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Does Homework Improve Academic Achievement?

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Educators should be thrilled by these numbers. Pleasing a majority of parents regarding homework and having equal numbers of dissenters shouting "too much!" and "too little!" is about as good as they can hope for.

But opinions cannot tell us whether homework works; only research can, which is why my colleagues and I have conducted a combined analysis of dozens of homework studies to examine whether homework is beneficial and what amount of homework is appropriate for our children.

The homework question is best answered by comparing students who are assigned homework with students assigned no homework but who are similar in other ways. The results of such studies suggest that homework can improve students' scores on the class tests that come at the end of a topic. Students assigned homework in 2nd grade did better on math, 3rd and 4th graders did better on English skills and vocabulary, 5th graders on social studies, 9th through 12th graders on American history, and 12th graders on Shakespeare.

Less authoritative are 12 studies that link the amount of homework to achievement, but control for lots of other factors that might influence this connection. These types of studies, often based on national samples of students, also find a positive link between time on homework and achievement.

Yet other studies simply correlate homework and achievement with no attempt to control for student differences. In 35 such studies, about 77 percent find the link between homework and achievement is positive. Most interesting, though, is these results suggest little or no relationship between homework and achievement for elementary school students.

Why might that be? Younger children have less developed study habits and are less able to tune out distractions at home. Studies also suggest that young students who are struggling in school take more time to complete homework assignments simply because these assignments are more difficult for them.

These recommendations are consistent with the conclusions reached by our analysis. Practice assignments do improve scores on class tests at all grade levels. A little amount of homework may help elementary school students build study habits. Homework for junior high students appears to reach the point of diminishing returns after about 90 minutes a night. For high school students, the positive line continues to climb until between 90 minutes and 2½ hours of homework a night, after which returns diminish.

Beyond achievement, proponents of homework argue that it can have many other beneficial effects. They claim it can help students develop good study habits so they are ready to grow as their cognitive capacities mature. It can help students recognize that learning can occur at home as well as at school. Homework can foster independent learning and responsible character traits. And it can give parents an opportunity to see what's going on at school and let them express positive attitudes toward achievement.

Opponents of homework counter that it can also have negative effects. They argue it can lead to boredom with schoolwork, since all activities remain interesting only for so long. Homework can deny students access to leisure activities that also teach important life skills. Parents can get too involved in homework -- pressuring their child and confusing him by using different instructional techniques than the teacher.

My feeling is that homework policies should prescribe amounts of homework consistent with the research evidence, but which also give individual schools and teachers some flexibility to take into account the unique needs and circumstances of their students and families. In general, teachers should avoid either extreme.

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Study: Homework Doesn’t Mean Better Grades, But Maybe Better Standardized Test Scores

Robert H. Tai, associate professor of science education at UVA's Curry School of Education

The time students spend on math and science homework doesn’t necessarily mean better grades, but it could lead to better performance on standardized tests, a new study finds.

“When Is Homework Worth The Time?” was recently published by lead investigator Adam Maltese, assistant professor of science education at Indiana University, and co-authors Robert H. Tai, associate professor of science education at the University of Virginia’s Curry School of Education , and Xitao Fan, dean of education at the University of Macau. Maltese is a Curry alumnus, and Fan is a former Curry faculty member.

The authors examined survey and transcript data of more than 18,000 10th-grade students to uncover explanations for academic performance. The data focused on individual classes, examining student outcomes through the transcripts from two nationwide samples collected in 1990 and 2002 by the National Center for Education Statistics.

Contrary to much published research, a regression analysis of time spent on homework and the final class grade found no substantive difference in grades between students who complete homework and those who do not. But the analysis found a positive association between student performance on standardized tests and the time they spent on homework.

“Our results hint that maybe homework is not being used as well as it could be,” Maltese said.

Tai said that homework assignments cannot replace good teaching.

“I believe that this finding is the end result of a chain of unfortunate educational decisions, beginning with the content coverage requirements that push too much information into too little time to learn it in the classroom,” Tai said. “The overflow typically results in more homework assignments. However, students spending more time on something that is not easy to understand or needs to be explained by a teacher does not help these students learn and, in fact, may confuse them.

“The results from this study imply that homework should be purposeful,” he added, “and that the purpose must be understood by both the teacher and the students.”

The authors suggest that factors such as class participation and attendance may mitigate the association of homework to stronger grade performance. They also indicate the types of homework assignments typically given may work better toward standardized test preparation than for retaining knowledge of class material.

Maltese said the genesis for the study was a concern about whether a traditional and ubiquitous educational practice, such as homework, is associated with students achieving at a higher level in math and science. Many media reports about education compare U.S. students unfavorably to high-achieving math and science students from across the world. The 2007 documentary film “Two Million Minutes” compared two Indiana students to students in India and China, taking particular note of how much more time the Indian and Chinese students spent on studying or completing homework.

“We’re not trying to say that all homework is bad,” Maltese said. “It’s expected that students are going to do homework. This is more of an argument that it should be quality over quantity. So in math, rather than doing the same types of problems over and over again, maybe it should involve having students analyze new types of problems or data. In science, maybe the students should write concept summaries instead of just reading a chapter and answering the questions at the end.”

This issue is particularly relevant given that the time spent on homework reported by most students translates into the equivalent of 100 to 180 50-minute class periods of extra learning time each year.

The authors conclude that given current policy initiatives to improve science, technology, engineering and math, or STEM, education, more evaluation is needed about how to use homework time more effectively. They suggest more research be done on the form and function of homework assignments.

“In today’s current educational environment, with all the activities taking up children’s time both in school and out of school, the purpose of each homework assignment must be clear and targeted,” Tai said. “With homework, more is not better.”

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November 20, 2012

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Study: Homework linked to better standardized test scores

Researchers who looked at data from more than 18,000 10th-graders found there was little correlation between the time students spent doing homework and better grades in math and science courses. But, according to a study on the researc h, they did find a positive relationship between standardized test performance and the amount of time spent on homework.

The study , called ”When Is Homework Worth the Time?: Evaluating the Association Between Homework and Achievement in High School Science and Math,” was conducted by Adam Maltese, assistant professor of science education at the Indiana University School of Education; Robert H. Tai, associate professor of science education at the Curry School of Education at the University of Virginia, and Xitao Fan, dean of education at the University of Macau.

According to a news release by Indiana University, the researchers looked at survey and transcript data from the students in an effort to explain their academic performance and concluded that despite earlier research to the contrary, homework time did not correlate to the final course grade that students received in math and science classes.

The value of homework has been the subject of various research studies over the years, yet there is still no conclusive evidence that it makes a big difference in helping students improve achievement. The most often-cited studies are those that conclude that there is virtually no evidence that it helps in elementary school but some evidence that it does improve academic performance in later grades. Yet this newest study looked at 10th graders and found no correlation.

The study did, however, find a positive association between time spent on homework and student scores on standardized tests. It doesn’t directly conclude that the homework actually affected the test scores, but the university release quotes Maltese as saying that “if students are spending more time on homework, they’re getting exposed to the types of questions and the procedures for answering questions that are not so different from standardized tests.”

That, of course, would depend on the kind of homework students receive. Maltese is further quoted as saying, “”We’re not trying to say that all homework is bad. It’s expected that students are going to do homework. This is more of an argument that it should be quality over quantity. So in math, rather than doing the same types of problems over and over again, maybe it should involve having students analyze new types of problems or data. In science, maybe the students should write concept summaries instead of just reading a chapter and answering the questions at the end.”

The co-authors also recommend that education policymakers better evaluate homework — the kinds of assignments that are most useful and the time required to make the work effective.

You may also be interested in this : 3 Healthy Guidelines for Homework

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Strategizing resources leads to improved exam scores, according to Stanford scholars

A study from Stanford psychology scholars found that college students employing a strategic approach to the use of study resources improved their exam scores by an average of one-third of a letter grade.

Patricia Chen is lead author on a paper that shows that a psychological intervention encouraging students to use available study resources in a strategic way made them more likely to perform better in class. (Image credit: L.A. Cicero)

Despite access to a trove of learning resources – including textbooks, online references and homework assignments – some students routinely fall short of their performance expectations.

The solution may not be to work harder, but more strategically. That’s the key takeaway from new research led by Stanford scholars, whose study published in Psychological Science found that applying a strategic approach to studying helped college students improve their exam scores by an average of one-third of a letter grade.

Inspiration to strategize

The study was inspired by meetings that lead author Patricia Chen, a postdoctoral research fellow in Stanford’s Department of Psychology , had with less-than-enthused students after they received their exam grades. Many of these students, she noticed, lamented their poor performances despite the great deal of effort that they had put into studying. The classic complaint seemed to be, “I studied really hard, and I’m just as smart as [another student]. I don’t understand why I didn’t do well.”

In response, Chen would ask these students, “Describe to me how you studied for the exam.” From the responses, Chen gleaned the insight that many students – intelligent and willing to work hard – fall short of performing to their potential because they don’t employ a strategic approach to their learning.

“Blind effort alone, without directing that effort in an effective manner, doesn’t always get you to where you want to go,” Chen said.

Power of self-reflection

The research team, which included Desmond Ong, a Stanford doctoral student in psychology, homed in on one important aspect of strategic learning – engaging in self-reflection to identify and use resources wisely. Prior research supports the general use of metacognition, or “thinking about one’s own thinking,” as a successful means to better learning and academic performance. But, before their studies, it remained to be seen whether specifically strategizing about one’s resource use would causally improve students’ academic performance.

The researchers developed a “Strategic Resource Use” intervention that blends educational and social psychological theories. The intervention, according to the study, “prompts students to think deliberately about how to approach their learning effectively with the resources available to them.”

The intervention was administered through brief online surveys sent to college students in an introductory statistics class about one week before their exams.

Students in the control group received a business-as-usual exam reminder. Students in the intervention group received the same exam reminder and a short Strategic Resource Use exercise: They were asked to think about what they expected to be on the upcoming exam and then strategize what kinds of resources they would use to study most effectively. Following this, the students were asked to explain why each resource they chose would be useful to their learning and then describe how they planned on using their chosen resources.

In two studies, students who strategized their resource use before studying outperformed comparable classmates in the control group by an average of one-third of a letter grade in the class. In the first study, students scored an average of 3.45 percentage points higher in the class, and in the second study, the average difference was 4.65 percentage points.

Why was the intervention so effective? The researchers found that the brief intervention exercise made students more self-reflective about how they approached their learning. In turn, this metacognition enabled students to use their resources more effectively, as their self-reports showed.

“It’s not merely about using a greater number of resources for studying. The important point here is using resources more effectively,” stressed Ong.

This strategic thinking also provided students with other psychological benefits, including feelings of empowerment regarding their education. Students who had taken the intervention perceived a greater control over their learning and expressed fewer negative feelings about their upcoming exams.

Chen emphasized it is important to consider the specific class environment before implementing the Strategic Resource Use intervention. The researchers note that the intervention has been tested – and found effective – in resource-rich environments, where students have access to textbooks, lecture notes, online resources, teaching assistants and other tools. But it is still unknown how well the intervention would work in resource-scarce environments. In resource-scarce environments, said Chen, it might be better for educators to focus on providing “a basic repertoire of resources” first.

A strategy for life

Chen proposes that the principle behind Strategic Resource Use can be applied beyond academics, including parenting, losing weight or learning a new skill at work.

“Actively self-reflecting on the approaches that you are taking fosters a strategic stance that is really important in life,” she said. “Strategic thinking distinguishes between people of comparable ability and effort. This can make the difference between people who achieve and people who have the potential to achieve, but don’t.”

Chen offered one more piece of advice: “Strategize how you want to effectively direct your efforts before you pour your energy into it.”

The study, “Strategic Resource Use for Learning: A Self-Administered Intervention That Guides Self-Reflection on Effective Resource Use Enhances Academic Performance,” was also co-authored by Omar Chavez, a graduate student at the University of Texas, and Brenda Gunderson, a senior lecturer at the University of Michigan.

Gray Matters: What role should homework play in learning?

Historical Background In the U.S., debates about the value of homework have been steady over the past century. In the beginning half of the 1900’s, homework was not nearly as common. Many school districts banned homework at the elementary and middle school levels in the belief that it only facilitated rote learning. That changed in the 1950’s when the Soviet Union launched Sputnik, creating the perception that the U.S. needed to increase the amount of students’ homework to be competitive in the space race. Over the next 50 years until the present, the popular view of homework switched every 15 years or so between support and condemnation. Today research has enhanced our understanding, but the debate continues.

Homework: What’s the Point? Numerous benefits are attributed to homework: better retention of factual knowledge, development of study habits, increased ability to manage time effectively, and heightened parental involvement. Evaluating exactly what of these benefits can be attributed to homework versus inherent differences in students or the quality of assignments presents obvious challenges. Further confounding research, homework often exacts costs in the form of increased stress and reduced sleep, which can negate potential benefits. Nonetheless, research to date provides guidance on homework’s role in achieving some of these goals.

Research Examples How much homework should be assigned? Although not unanimous, multiple studies on the relationship between homework time and academic achievement have shown that it is not a linear relationship: more homework does not equal more learning. One study of 7,451 13- year-old students administered a test of science and mathematics in addition to a survey of effort spent on homework, homework time, homework frequency, and the general circumstances around how homework was done. Results: student academic gains were associated with homework time up to 1 hour a day, after which increased homework time was associated with worse performance. This result varies with students’ ages.

How does the influence of homework change in different grades? While empirical studies have not yet explicitly compared the role of homework in different ages, a review of the literature reveals clear trends. A meta-analysis of 4,400 studies up until 2003 found that homework time had different effects depending on the grade of students. Results: up to two hours of homework showed the most benefit for high school students, up to an hour of homework showed some benefit for middle school students, and almost no benefit was found among elementary school students.

What homework factors contribute to academic performance? Studies that focus on the circumstances in which students complete homework have found that autonomy and effort are more important predictors of performance than homework time alone. One study of 483 eighth-graders from 20 classes analyzed students’ grades and standardized test scores in mathematics in relation to survey responses on homework effort. Students responded once in November and once in May of the academic year. Results: academic gains in grades and test scores were positively correlated to homework effort. However, other studies suggest that since effort and autonomy are highly correlated with students’ prior achievement, it’s difficult to say if this is a trait of the homework or of a certain kind of student.

How can homework best facilitate learning? Practices from the “ How can I improve longterm learning ” edition of Gray Matters 01 should be implemented in homework design to facilitate learning. For instance, using homework to continue practice on material and skills learned in previous weeks uses distributed practice to improve recall. Homework that offers adequate practice of important skills also helps reinforce skills in a variety of contexts. A survey of school leaders around homework best practices found similar results: homework can facilitate engagement when it is an authentic, engaging extension of the class. Results: homework should be designed intentionally, with reference to most effective forms of practice.

Does the effect of homework change when instruction occurs at home and exercises are done in class? In this case, the question is essentially if homework facilitates learning when it is done as a part class rather than at home. One model that represents this circumstance is the flipped classroom. Case studies done with ninth to twelfth-graders across a variety of subjects showed that achievement increased after implementing a model where students watched videos at home and practiced learning in class. In these schools the percentage of students passing standardized exams increased by up to 12%. Empirical studies comparing in-class work and at home work have repeated research design flaws, however, they generally indicate that in-class exercises have a positive effect for older students. Results: the research is inconclusive, but generally indicates that flipped classroom approaches have positive net benefits for high school students.

How frequently should homework be assigned? The research on frequency is not conclusive, however most studies suggest that classes that receive homework frequently tend to do better on tests of achievement. One such study administered standardized mathematics examinations to 2,939 grade 7 and 8 students across 20 classes. In addition to the exam, students answered questions on frequency of homework and the average amount of time spent on homework each evening. Results: Classes that had more frequent homework assignments had overall higher averages on the achievement tests.

Does homework change students’ attitudes towards school? Studies comparing the attitudes of students who received homework with those who did not receive homework generally found no significant results across a variety of grade levels. One study compared three different models for assigning arithmetic homework to 342 third-graders across twelve classrooms: teachers assigned no homework, assigned homework as usual, and were required to assign a constant amount of homework every night. Students answered questions measuring their attitudes towards school, teacher, arithmetic, spelling, reading, and homework. Results: no significant differences were found between the attitudes of the different groups.

Conclusion The quality of homework and the students who complete it vary significantly, however the general research trends suggest that assigning homework does have benefits at the middle and upper school levels. Frequency of assignment and students’ autonomy in finishing homework were also correlated with student achievement. These results provide guidelines on the appropriate quantity of homework, but how best to incorporate homework content into an overall progression of students’ learning remains for teachers to judge.

“Adolescents’ Homework Performance in Mathematics and Science: Personal Factors and Teaching Practices” by Rubén FernándezAlonso, Javier Suárez-Álvarez, and José Muñiz, Journal of Educational Psychology , 2015, 107(4), 1075.

“Ask the Cognitive Scientist Allocating Student Study Time” by Daniel T. Willingham, American Educator , 2002, 26(2), 37-39.

“Does Homework Improve Academic Achievement? A Synthesis of Research, 1987–2003” by Harris Cooper, Jorgianne Civey Robinson, and Erika A. Patall, Review of Educational Research , 2006, 76(1), 1-62.

“Does Homework Improve Learning?” by Alfie Kohn, AlfieKohn.org, 2006. “Effects of Arithmetic Homework upon the Attitudes of Third Grade Pupils Toward Certain School-related Structure” by Norbert Maertens, School Science and Mathematics , 1968, 68(7), 657-662.

“Flipped Learning Model Dramatically Improves Course Pass Rate for At-Risk Students, Clintondale high School, MI: A Case Study” by Pearson Education, May, 2013.

“Flipped Learning Model Increases Student Engagement and Performance, Byron High School, MN: A Case Study” by Pearson Education, June, 2013.

“Homework. Research on Teaching Monograph Series, Homework Versus In-class Supervised Study” by Harris Cooper, 1989, 77- 89.

“If They’d Only Do Their Work!” by Linda Darling-Hammond and Olivia Ifill-Lynch, Educational Leadership, 2008, 63(5), 8-13.

“Research Trends: Why Homework Should Be Balanced” by Youki Terada, Edutopia, 2015, July 31.

“Synthesis of Research on Homework” by Harris Cooper, Educational leadership, 1989, 47(3), 85-91.

“The Homework–Achievement Relation Reconsidered: Differentiating Homework Time, Homework Frequency, and Homework Effort” by Ulrich Trautwein, Learning and Instruction, 2007, 17(3), 372-388.

Gray Matters is dedicated to providing research-based answers to questions commonly raised by faculty and within the education community. Gray Matters is published by the Tiger Works Research & Development group at Avenues.

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School of education study: homework doesn’t improve course grades but could boost standardized test scores.

Thursday, November 15, 2012

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Spending Too Much Time on Homework Linked to Lower Test Scores

A new study suggests the benefits to homework peak at an hour a day. After that, test scores decline.

Samantha Larson

Polls show that American public high school teachers assign their students an average of 3.5 hours of homework a day . According to a  recent study from the University of Oviedo in Spain, that’s far too much.

While doing some homework does indeed lead to higher test performance, the researchers found the benefits to hitting the books peak at about an hour a day. In surveying the homework habits of 7,725 adolescents, this study suggests that for students who average more than 100 minutes a day on homework, test scores start to decline. The relationship between spending time on homework and scoring well on a test is not linear, but curved.

This study builds upon previous research that suggests spending too much time on homework leads to higher stress, health problems and even social alienation. Which, paradoxically, means the most studious of students are in fact engaging in behavior that is counterproductive to doing well in school. 

Because the adolescents surveyed in the new study were only tested once, the researchers point out that their results only indicate the correlation between test scores and homework, not necessarily causation. Co-author Javier Suarez-Alvarez thinks the most important findings have less to do with the  amount of homework than with how that homework is done.

From Education Week :

Students who did homework more frequently – i.e., every day – tended to do better on the test than those who did it less frequently, the researchers found. And even more important was how much help students received on their homework – those who did it on their own preformed better than those who had parental involvement. (The study controlled for factors such as gender and socioeconomic status.)

“Once individual effort and autonomous working is considered, the time spent [on homework] becomes irrelevant,” Suarez-Alvarez says. After they get their daily hour of homework in, maybe students should just throw the rest of it to the dog.  

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Samantha Larson is a freelance writer who particularly likes to cover science, the environment, and adventure. For more of her work, visit SamanthaLarson.com

SiOWfa15: Science in Our World: Certainty and Controversy

The course website and blog for the fall 2015 instance of penn state's sc200 course.

Does Homework Promote Academic Achievement?

We all hate homework. It’s tedious, frustrating, time-consuming, and downright horrible. Sometimes we get points for doing homework and doing well which is always a good reason for getting it done, but could success on homework be the reason for fantastic final grades?

Let’s establish the basics of what we are trying to find here. The x-variable is doing your homework while the y-variable is earning excellent grades. Confounding, z-variables , could include personality traits, lack of procrastination habits, natural ability to succeed in school, etc. Our null hypothesis  is that doing your homework does not improve your final grade . Our alternative hypothesis is that doing your homework does improve your final grade and promotes academic achievement.

Harris Cooper , a professor of psychology and neuroscience at Duke University, and his colleagues compiled an analysis of dozens of studies done on homework in order to come to a conclusion on whether homework is effective. If it is effective, how much homework is too much, and what is the appropriate amount to give out to students?

Many of the studies done on this question examine students who are assigned homework with students who are not assigned homework but are still similar in other ways. Interestingly, many of the results found that homework can improve test scores at the end of a topic. “Students assigned homework in 2nd grade did better on math, 3rd and 4th graders did better on English skills and vocabulary, 5th graders on social studies, 9th through 12th graders on American history, and 12th graders on Shakespeare.” ( Cooper )

Some studies do not attempt to control for student differences. 35 studies suggest that 77% find the correlation between homework and and academic achievement to be positive; however, they fail to make this correlation among elementary students. One possible solution to control for student differences would be to randomly distribute the students based on similarities so that on average, both the homework group and the non-homework group are about the same in terms of similarities, i.e. learning disabilities, gender, and prior achievement in school. Additionally, Cooper says an explanation for why there is not a correlation among elementary students could be because they do not have well developed study habits and because they get distracted easily.

In short, Cooper suggests that through his analysis, homework is in fact beneficial to students . Not only can it have positive effects on overall grades, but it can also have other benefits such as developing responsible character traits, maturing cognitive capacities, fostering independent learning habits, and growing of good study habits. Cooper, along with most educators, says homework should not exceed 10-20 minutes for children K-2, 30-60 minutes a day for grades 3-6, and varying times depending on the subjects for middle school and high school students.

Some feel that homework can have many negative effects such as developing a disinterest in school among students, homework denies children of leisure time and takes them away from extra-curricular activities which also teach important life skills. It is important to allow teachers and administrators to have flexibility to account for the differences in some students and their families; however, sticking to the prescribed regiment is most effective for most students.

Rival ACC school, the University of Virginia, has a much different take on homework than Cooper. Co-authors Adam Maltese, assistant professor of science education at Indiana University, Robert H. Tai, associate professor of science education at the University of Virginia’s Curry School of Education, and Xitao Fan, dean of education at the University of Macau, conducted their own studies and published “ When Is Homework Worth the Time ?”

Because the paper is twenty-two pages long, I will summarize the findings. If you would like to, the full report can be read here . 18,000, tenth grade students’s survey and transcript data were observed in the study collected from 1990 to 2002 by the National Center for Education Statistics . Unlike many studies done on homework and final grades, Maltese, Tai, and Fan found that time spent on homework did not effect the final course grade among those who did and did not do their homework. Conversely, they did find a correlation between time spent on homework and success on standardized test scores. Maltese says, “Our results hint that maybe homework is not being used as well as it could be.” In order to be more effective with homework, teachers should assign homework which is useful, sort of a quality over quantity  type of thing. Rather than give a designated amount of homework, give assignments which will keep the students engaged for a short period of time and allow for a greater chance of retaining that information. In effect, this will also allow for appropriate amounts of time to be allocated towards extracurricular activities which teach young people other valuable lessons while also learning from engaging homework.

All of this raises the question: what is the most effective type of homework assignment? I certainly feel as though this question can best be answered based on each individual person. Because some people are inherently auditory, visual, or hands-on learners, one standard type of homework cannot be called the best . I believe in order to really get the best result from everyone, each person would require their own homework regiment. Seeing as though some schools have entire graduating classes of well-over 2,000 students , creating an individualized homework regiment for each student is simply impossible. So what basic principles should teachers and administrators use to create effect homework?

The Association for Supervision and Curriculum Development ( ASCD ) attempted to tackle this tricky question with their “ Five Hallmarks of Good Homework .” The first principle is purpose . Students must be given a clear end goal to their assignment such as giving simple division problems in order to understand the concept of division or writing sentences using certain vocabulary words so that students can understand the context of those specific vocabulary words. In addition, ASCD says practice is most effective when given in small doses over long periods of time, concurrent with Maltese, Tai, and Fan. The second principle is efficiency . ASCD says projects which involve cutting, gluing, and constructing are often extremely inefficient even though the teacher has great intentions when they assign them because they are fun and creative. Instead, rather than making a poster, students should be tasked to put themselves in the perspective of their project. For example, ASCD suggests if students are tasked with a history assignment, they should be asked to create a diary entry as if they were the person who experienced what they are trying to learn (writing about what it was like to immigrate from another country, writing about what World War 2 was like, etc.). The third principle is ownership . One of the easiest ways to promote ownership is by giving flexibility. Instead of prescribing a common book for the class to read, teachers could allow students to find their own sources such as magazines and academic journals which are still relevant to the topic. This keeps the students engaged and interested in what they are learning. “Instead of worrying about whether students did the reading, we should be focusing on whether the reading did them any good” ( ASCD ). The fourth principle is competence . Because, each student is different, they should be allowed to work together if they choose to and receive help on assignments. Students often get discouraged when forced to work alone and are more likely not to complete a task. The fifth, and final, principle is aesthetic appeal . First impressions are extremely important to students. As soon as they see the requirements and details of an assignment, they make a snap decision about whether they are going to do it or not and, if they are going to do it, how well they are going to do it. Students are more inclined to complete an assignment which are visually uncluttered with few information on the page. Lots of room to write answers and the use of graphics and clip art on the page are also quite appealing to students. Visuals are just as important to the student as knowing they have little work to do.

Take home message: homework is beneficial to the student in more ways than just improving final grades but only when allocated effectively . In my opinion, and I think most would agree, there need to be more studies done on the effectiveness of homework. Preferably, some kind of experimental study would be conducted to almost definitively prove that effective homework benefits the student in multiple ways. Of course, a double-blind placebo would be out of the question because the student would know if they are doing their homework or not. Maybe a single-blind study could be effective where the students are randomly placed into two groups, homework and no homework. The teacher would not know who is and who is not doing their homework, but would still assign regular assignments to the class. The students either do or do not complete their homework, and at the end of the semester or grading period, examine the results of how many students received good or bad marks on their final reports. Of course, this study would flawed in that if a student gets placed into the group who does not do their homework but normally would have done their homework and their grade suffers from not doing it, that is infringing on the student’s ability and right to learn, and compromises their own responsibility for their grades; however, at this point, this is the closest I could get to an appropriate experimental study. Any other suggestions would be greatly appreciated in the comments.

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Very interesting post. In high school, I was adamantly anti-homework, generally equating homework with meaningless busywork, but your post got me thinking, and I came up with an idea for a study that sort of expands on your idea. Here’s what I’ve got: a class made specially for the study is split into two groups via random assignment, and one group is assigned homework while the other is told not to do the homework. The study will include a random sample of students of the same grade level or year, and everyone will come to class as required and will be encouraged to be active in the classroom and really pay attention to what is being taught (the teacher will find a way to get around to this somehow). Besides the homework, the only real assignments given are in-class quizzes and a final at the end of the semester, which is when the grades of those who did and didn’t do the homework will be compared. The homework, of course, will be GOOD homework, as determined by the five hallmarks you went over in your post. Also, this class will institute a NO-STUDY policy. That’s important. It will be physically impossible to study for the tests anyway, because there is nothing that students can read or study from at home — no handouts, nothing. (The entire curriculum may as well be completely fabricated.) This study is far from a perfect setup and I’m sure it contains some major flaws in reasoning, the most obvious of which is the question of the students’ drive and motivation to actually try on the homework in the first place (since this won’t be a class that they’re technically graded on, so it may not be a true measure of their aptitude and ability… but that’s still better than the alternative). Anyhow, I could see it turning up some interesting results. Given that the homework demonstrates the strongest possible examples of the five hallmarks of good homework, and the students assigned homework put forth their best effort on the homework assignments, I think that the homework-assigned group could receive better overall grades than the no-homework group.

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Just do it! Study time increases mathematical achievement scores for grade 4-10 students in a large longitudinal cross-country study

Markus wolfgang hermann spitzer.

Institute of Psychology, Albert-Ludwigs-Universität Freiburg, 79085 Freiburg, Germany

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All data will be available on https://osf.io/ .

Decades of research produced inconsistent findings on whether study time can lead to achievement gains in mathematics. Data generated by more than six thousand students from three different countries who solved more than 1.1 million problem sets using a dedicated mathematics software are analyzed regarding the effect of study time on students’ achievements in mathematics. Results showed that more study time led to higher performance scores in mathematics. Further analyses revealed that low-performing students in the first school year (2017-2018) who increased their study time in the following year (2018-2019) revealed greatest gains in performance in the same school year (2018-2019) and even in the year after (2019-2020). Finally, results replicated previous observations of robust performance scores within students over the three school years, with performance scores in 2017-2018 predicting those of 2018-2019 which predicted those of 2019-2020. These results support the idea that students, in particular low-performing students, can boost their academic abilities to upper levels when increasing their study time.

Introduction

Children and adolescents who reach high levels of mathematical abilities early in life persist on these levels over time (Aunio and Niemivirta, 2010 ; Jordan et al., 2011 ; Siegler et al., 2012 ; Watts et al., 2014 ). Furthermore, strong mathematical abilities at young age are related to a higher socio-economic status and higher salaries during adulthood (Murnane et al., 1995 ; Ritchie and Bates, 2013 ; Rivera-batiz, 1992 ). However, the number of students who do not achieve ordinary mathematical skills at the end of high-school is troubling (Moore et al., 2010 ). These observations raise the challenge on the best way to boost mathematical abilities in poorly performing children and adolescents (National Mathematics Advisory Panel, 2008 ).

One major unresolved question in the search for factors that promote students’ mathematical abilities is whether increases in study time lead to gains in mathematical achievement scores. While decades of research have demonstrated that the accumulated hours spent with deliberate practice determined successful acquisition of knowledge and skills in other domains, such as for professional violinists (Ericsson et al., 1993 ), chess players (Krampe and Ericsson, 1996 ), and soccer players (Roca et al., 2012 ; Ward et al., 2007 ), results from studies on whether study time leads to increased knowledge and achievement scores in education are inconsistent (Jez and Wassmer, 2015 ; Macnamara et al., 2014 ; Pittman et al., 1986 ; Plant et al., 2005 ; Schuman et al., 1985 ). This provided the motivational background for the present investigation of the effects of study time on mathematical achievement scores using a large longitudinal dataset from three different countries. In the following sections, we overview literature on effects of study time on academic achievement scores.

Effects of study time on academic achievement scores

Plant et al. ( 2005 ) observed that prior abilities and self-regulation skills, but not study time, influenced grade point average scores of college students. Furthermore, they observed that the quality of study time differed between students (Plant et al., 2005 ; for similar results see Schuman et al., 1985 ). Another study reported that effort and not study time predicted academic outcomes best (Flunger et al., 2015 ). A recent meta-analysis revealed that study time only explained 4% of the variance of educational outcomes (Macnamara et al., 2014 ). Moreover, the importance of self-regulatory skills on achievement scores have been highlighted by others (Schunk and Zimmermann, 1997 ; Zimmerman and Kitsantas, 2005 ). In line with these observations, no significant difference between students’ academic achievement scores was observed for students with a reduced academic school year of 20 days, compared to students with a regular school year (Pittman et al., 1986 ). In contrast to these findings, Jez and Wassmer ( 2015 ) reported that study time had a positive impact on high-school students’ academic achievement scores, and in particular, that low-performing students benefit the most from extra study time (Jez and Wassmer, 2015 ). On a similar account, Doumen et al. ( 2014 ) report that study time influenced course grades of college students (Doumen et al., 2014 ). In addition, a positive correlation between grand average college scores and study time (Gortner-Lahmers and Zulauf, 2000 ) and the positive effects of deliberate practice on academic achievement scores have been reported (Eskreis-Winkler et al., 2016 ).

Whereas the dependent variable in these studies was grand point average scores, others narrowed their research on the effects of study time specifically on mathematical achievement scores of middle school students. For example, several studies reported a positive correlation between study time on homework assignments in mathematics and learning achievements (Cheema and Sheridan, 2015 ; Cooper et al., 2006 ; Cooper and Valentine, 2001 ). However, others did not observe a positive effect of homework study time on students’ achievement gains in mathematics (Flunger et al., 2015 ; Trautwein, 2007 ). Several other studies argue that the quality of study time and not just the quantity influence the effect of study time on mathematical achievement (Perels et al., 2009 ; Rosário et al., 2013 ). For instance, Rosário et al., ( 2013 ) investigated the effects of study time on mathematical achievement in 1300 middle school students. They observed that factors such as self-regulatory learning scores and motivational factors mediated the effect of study time on mathematical achievement.

In sum, the literature yields inconsistent results regarding the effect of study time on mathematical achievement gains. While few studies observed a positive correlation between study time and achievement scores, others observed that the positive effect of study time is mediated by factors such as self-regulatory skills and motivational factors (Rosário et al., 2013 ), effort (Flunger et al., 2015 ; Schuman et al., 1985 ; Trautwein, 2007 ), and the quality of study time (Perels et al., 2009 ; Rosário et al., 2013 ). Furthermore, it is not yet clear whether more study time alone can enhance the achievement scores of low-performing students, and whether these gains of low-performing students’ due to increased study time are sustainable and persist over longer periods of time.

From a methods point of view, it appears important to note that the studies reviewed above investigated the influence of study time, by means of a questionnaire, on academic achievement scores on tests after the study time. Given the generally poor reliability of self-reported questionnaire estimates, it may be better to assess study time directly with the use of computer-based measurements of study time. In the following section, we outline advantages of online learning environment when measuring study time and achievement scores.

Online learning environments enrich measurement possibilities

A major advantage of online learning environments is the possibility to analyze massive amounts of collected data with precise measures such as the time students spent completing problem sets, students’ results on these problem sets, and the date on which problem sets were completed (Koedinger et al., 2007 ; Koedinger et al., 2015 ). In addition, these data can be analyzed within long-term investigations on how students’ mathematical abilities develop over years of schooling, and which factors influence these learning trajectories (Baker and Inventado, 2016 ).

For instance, Louw et al. ( 2008 ) made use of these technological advantages and analyzed the data collected with a dedicated mathematics software package. They examined the achievements in mathematics of students from three different schools using a mathematical software over several months. Thereby, they were able to show a positive correlation between amount of study time with the software and students’ improvement scores between grades eleven and twelve (Louw et al., 2008 ). However, the authors noted that software usage time was generally very low, with an average of less than 3 h of math training spent with this software within 5 months. Moreover, their results do not distinguish between students with weak mathematical abilities and students with strong mathematical abilities. Therefore, it remains unclear if such a training approach can be specifically beneficial to weaker students. In this investigation, we made use of a software learning tool for mathematics which shall be briefly described.

The Bettermarks software

We analyzed the data collected with the software package Bettermarks within the time frame of three consecutive school years (year 1: 2017/2018; year 2: 2018/2019; year 3: 2019/2020). The Bettermarks software is a mathematical learning software that is currently (as of March 2020) used as a complement or even supplement to traditional math books in over 600 schools and over 5000 classes across Germany, Uruguay, and the Netherlands. The software comprises over 100 “book topics” (i.e., general topics, such as “Basics calculations of fractions,” or “Advanced calculations of fractions”) that comprise over 2000 different problem sets from classes 4-10 in four different languages (German, English, Spanish, and Dutch), with the highest usage in Germany, Uruguay, and the Netherlands. Each of the book topics was created in close relation to the curricular of each country, respectively. Put in other words, book topics represent the curricular of the school system in each country, respectively. Each book topic consists of an introduction page to the mathematical topic and 12 problem sets on average and each of these problem sets consist of eight distinct mathematical problems on average. Bettermarks is used within the class context, meaning that teachers assign problem sets to students within the software (just as they would with traditional math books). Students compute these assigned problem sets and receive immediate feedback on their result (correct/incorrect) for each problem. Furthermore, they receive the average score they reached on the particular problem sets after computing all individual problems in a problem set. For example, if a student computes 10 single mathematical problems within a problem set and gets 8 out of 10 answers correct, he receives feedback that his/her average score was 80%. Students are able to repeat a problem set; however, the parameterization changes on the next attempt. This new parameterization is necessary, because students could memorize the result of the first attempt to cheat on the new attempt by inserting the memorized answer of the system. Teachers are able to monitor the results of their students and are able to incentivize their students to perform as accurately as possible on the system by including the results in students’ oral grades. Students do not see the problem set before they select to compute them and thus, the process of selecting a problem set allows the precise measurement of the timepoint when students start to work on a mathematical problem set. When students finish the calculation of all single problems within a problem set, they press a proceed button, allowing the precise measure of the end timepoint of computing the problem set. Together, the software allows the collection of data on study time of problem sets and students’ performance on these problem sets in relation to other students’ performance on the same problem sets (see the “Data analysis” section for a detailed description on the performance measure).

Purposes of this study

Taken together, the reported studies suggest the need for a systematic investigation on study time on mathematical achievement in order to answer the following questions:

• Does study time in itself have a positive effect on mathematical achievement scores in K-12 students?
• Does study time boost performance for low-performing students in particular?
• Do increases in performance, due to more study time, persist over time?
• Does the quality of study time matter?

To find answers for these questions, we analyzed the average study time and the average performance score on problem sets students computed within three consecutive school years in three distinct analyses (see Table ​ Table1). 1 ). We first analyzed whether students’ study time in year 1 influenced their performance scores in this school year (analysis 1). Another analysis (analysis 2) was carried out to replicate the effect of study time on performance in year 2. In addition, this analysis investigated whether students’ performance in year 2 depended on the performance of the previous school year (year 1) and whether this dependency would interact with the amount of study time during this school year (year 2). In a final analysis (analysis 3), we tested whether students with a low performance in year 1, who increased their study time in year 2, also increased their performance in year 3. Furthermore, we examine whether the effect of study time differed between students who did improve, compared to students who did not improve while studying. More precisely, we tested whether low-performing students in year 1, who increased their study time in year 2, and did improve in year 2, varied in terms of their performance in year 3, from those low-performing students in year 1, who increased their study time in year 2, but did not improve their performance in year 2.

Dependent and independent variable(s) of each conducted analysis

Note: The main effects and all possible interactions were included in the linear regression models

We tested each analysis with students who used the software in Germany. Each analysis was also carried out for two further datasets collected from Uruguayan students, and Dutch students. The purpose of these replications was to test the robustness of the results obtained from the data from German students.

The Bettermarks software has been used in classrooms since 2008. The learning software allows teachers to assign problem sets from different book topics to students. Teachers use the software like a textbook inside the classroom and for homework assignments and they can freely choose which problem sets they want assign to the students of their class. Over 100 book topics cover over 2000 different problem sets of the curricula for students from grades 4-10 (age range: 9-16). The software can be used as a complement or supplement to traditional math books. High-school teachers use the software to either assign problem sets to students as homework, or as exercises within the classroom. The data from classroom or homework assignments were analyzed in this research project. The data is stored anonymized and thus any information relating the students with the data (e.g., students’ gender or age) cannot be obtained.

Inclusion criteria

The research project included data of students from three different countries (Germany, Uruguay, and the Netherlands) who used the software from September 1st, 2017, until March 1st, 2020, respectively. In addition to this time frame, five further inclusion criteria were applied. Data analysis only included (a) students from classes with more than 20 students; (b) students who used the software in each school year; (c) students who computed at least 50 distinct problem sets with the software; (d) answers from completed problem sets 1 ; and (e) problem sets completed by at least 30 students. These inclusion criteria were set prior to the data analysis and only the data of students who met these inclusion criteria was obtained from Bettermarks.

The obtained dataset comprised 4090 German students who computed a total of 406,396 problem sets, 351 Uruguayan students who computed 38,970 problem sets, and 1690 students from the Netherlands who computed 713,929 problem sets. In sum, the current research project comprised a total of 6131 students who computed a total of 1,159,295 problem sets.

Independent and dependent variables

Three independent variables described the study time (in hours) spent computing mathematical problem sets with the software for each student in each school year (measured from September 1st, until August 31st) labeled as time Year 1 , time Year 2 , and time Year 3 (interval scaled) 2 . In addition to these study time variables, we computed students’ performance on each problem set as dependent variables. The performance was calculated as follows. On each problem set, students achieved an accuracy score between 0 and 1. However, this accuracy score depended on the difficulty of the problem set. To account for problem set difficulty, we computed the average accuracy score of each problem set from results of all students (which we refer to as the population) on each problem set. For instance, if 30 students computed a particular problem set with an average accuracy of 80%, this accuracy score was then used as an estimate for problem set difficulty. The performance of each student was then calculated as students’ accuracy on a problem set minus the difficulty of this problem set. Positive performance scores indicate a result above the average accuracy of the population while negative performance scores indicate a result below the average accuracy of the population. Finally, the average performance scores of each student in each time window were computed and labeled as performance Year 1 , performance Year 2 , and performance Year 3 (interval scaled).

Data analysis

Effects were estimated with a linear regression model in the R environment for statistical computing (R Core Team, 2013 ; RStudio Team, 2015 ). Graphs were plotted with the sjPlot package (Lüdecke, 2020 ).

A linear regression estimated the influence of the independent variable time Year 1 on the dependent variable performance Year1 on German students, Uruguayan students, and Dutch students (analysis 1). We expected that students with increased study time revealed increased performance scores in all three analyses.

In the following analysis (analysis 2), we investigated the stability of students’ performance in mathematics between school years and whether the amount of study time in the following school year influenced students’ performance in this year. Therefore, we utilized students’ performance score of the first year (performance Year 1 ) as an independent variable and examined its effect on the performance score in the following year (performance Year 2 ). In addition, we included the independent variable time Year 2 to replicate the result of analysis 1. Finally, the interaction between the independent variables performance Year 1 and time Year 2 was added in the linear regression model. Again, the analysis was conducted for German students, Uruguayan students, and Dutch students. We expected that the performance Year 1 had a positive effect on the performance Year 2 , with students with low-performance scores in year 1 having low-performance scores in year 2 and students with high-performance scores in year 1 having high-performance scores in year 2. In addition, we expected that more study time in year 2 would lead to higher performance scores in year 2. Finally, we expected an interaction between time Year 2 and performance Year 1 , with study time having increased effects on students with low-performance scores in year 1, compared to students with high-performance scores in year 1.

In a final analysis (analysis 3), we investigated whether a beneficial effect of study time could have long-lasting effects. In addition, we sought to investigate the effect of the quality of study time. More precisely, it may be that an overall positive effect of study time is due to some students who increased their study time and actually studied their learning material while another proportion of students increased their study time, but simply sat in front of their study material without actually studying. To investigate this, we measured the quality of study time as the study time that led to increased performance scores within the same year. A linear regression model with the independent variables performance Year 1 (interval scaled), the performance Year 2 (interval scaled), and time Year2 (interval scaled) and the dependent variable performance Year 3 (interval scaled), with all main effects and all interaction effects of these independent variables, was carried out to test the hypotheses. We expected that the amount of study time in year 2 (2018-2019) influenced the performance score throughout the following school year (2019-2020). In addition, we expected a significant three-way interaction showing students with low-performance scores in school year 1 (2017-2018), with increasing study time in year 2 (2018-2019) and increasing performance scores in year 2 (2018-2019), revealing increased performance scores in year 3 (2019-2020). However, low-performing students in school year 1 (2017-2018), with increased study time in year 2 (2018-2019) but no increase in performance in the second school year, were expected to remain on low-performance scores in the third school year (2019-2020).

A summary of the descriptive statistics with the average study time and the average performance of each country and each school year, respectively, is provided in Table ​ Table2. 2 . The results of analysis 2 are depicted in Fig. ​ Fig.1 1 and results of analysis 3 are summarized in Fig. ​ Fig.2 2 and in Fig. ​ Fig.3 3 .

The average time in hours (time), standard deviation of time (time SD), average performance (performance), and standard deviation of performance (performance SD) for each country, and school year (year)

Year 2 performance in mathematics as a function of study time in hours in year 2 and performance in year 1. The more hours students studied in year 2, the higher the performance scores. This effect was more severe for students with weak performance scores in year 1 compared to students who already performed on a high level in year 1. The left panel graphs the results of German students. The right panel graphs the results of the combined datasets of Uruguayan students and students from the Netherlands. Blue-colored lines and shades indicate the model fits and standard error of the high quintile with the top 20% students of year 1. Red-colored lines and shades indicate the model fits and standard error of the low quintile with the weak 20% of the students of year 1

Year 3 performance in mathematics as a function of study time in hours in year 2, performance in year 1 (shown in colors for the three performance scores −.1, 0, .1) and performance in year 2 (shown in panels for the three performance scores −.1, 0, .1) for Germany (upper graph), Uruguay (middle graph), and the Netherlands (bottom graph). The more hours students spent to compute problem sets in year 2, the higher the performance in mathematics; however, if students’ performance scores increased in year 2, the study time spent was associated with steeper increases in performance scores (e.g., comparison between slope of red line on the left panel and red line on the right panel). Solid lines indicate the regression fits. Colored shades indicate the standard error of the mean

Students’ performance results of year 3 as a function of the extreme performance groups (quintiles) of year 1, and study time of year 2 for Germany (left) and the other two countries (right). Weak students who spent more time with the software revealed steeper performance gains in year 3 from more study time in year 2, compared to students who performed on high levels in year 1. Colored lines and shades indicate the model fits and standard errors, respectively

Analysis 1: performance Year 1 as a function of time Year 1

The performance of students in the first school year (2017-2018) significantly increased with increasing study time in this school year (Germany: b = 0.004; t (4088) = 13.88; p < .001), Uruguay ( b = .003; t (349) = 3.02; p = .002), and the Netherlands ( b = .0002; t (1688) = 2.36; p = .018).

Analysis 2: performance Year 2 as a function of performance Year 1 and time Year 2

Students’ performance during the first school year (2017-2018) significantly predicted their performance in the year after (Germany: b = .44; t (4086) = 17.11; p < .001; Uruguay: b = .41; t (347) = 4.25; p < .001; the Netherlands: b = .17; t (1686) = 3.34; p < .001). Moreover, the performance in year 2 significantly increased with increasing study time during the second year (Germany: b = .004; t (4068) = 11.67; p < .001; Uruguay: b = .004; t (347) = 3.68; p < .001; the Netherlands: b = .0008; t (1686) = 6.84; p < .001). The interaction between performance Year 1 and time Year 2 was not significant in any of the three analysis (Germany: b = −.003; t (4086) = −1.17; p = .238; Uruguay: b = −.002; t (347) = −0.18; p = .851; the Netherlands: b = .001; t (1686) = 1.18; p = .236). The lack of a significant interaction effect does not allow to conclude whether low-performing students in year 1 benefit more or less (in terms of performance in year 2) from extra study time in year 2 compared to high-performing students in year 1.

The non-significant interaction effect was further explored with two extreme performance groups of the first year: a low-performance group (bottom 20% of the performance students in year 1) and a high-performance group (upper 20% of the performance students in year 1). This quintile split was done for each of the three datasets. We used the German dataset for an exploratory analysis and aimed to replicate the observation made in this dataset with a combined dataset of Uruguayan and Dutch students 3 . Results indicated a significant interaction with a positive effect of more study time in year 2 on the performance in year 2, but a steeper increase of study time for those German students who performed low in year 1, compared to high-performance German students in year 1 ( b = −.002; t (1632) = −4.12; p <.001). The combined dataset only revealed a trend towards this effect ( b = −.0002; t (813) = −1.79; p = .073; see Fig. ​ Fig.1 1 ).

Analysis 3: performance Year 3 as a function of performance Year 1 , time Year 2 , and performance Year 2

The main effect of performance Year 1 was significant in Germany but not the other two countries (Germany: b = 0.255; t (4082) = 8.23; p < .001; Uruguay: b = 0.019; t (343) = 0.17; p = .85; the Netherlands: b = 0.072; t (1682) = 1.40; p = .159), suggesting that the performance of students in the first year predicted their performance 2 years later in Germany. The lack of a significant result in the other two countries may be due to the smaller size of the dataset. The main effect of performance Year 2 on performance Year 3 was significant in all three countries (Germany: b = 0.517; t (4082) = 19.68; p < .001; Uruguay: b = 0.687; t (343) = 4.60; p < .001; the Netherlands: b = 0.575; t (1682) = 9.06; p < .001), suggesting that students’ performance in year 2 predicted their performance in year 3. The main effect of time Year 2 on performance Year 3 was significant in Germany, but we only observed a trend of this result in the other two countries (Germany: b = 0.001; t (4082) = 5.29; p < .001; Uruguay: b = 0.002; t (343) = 1.78; p = .075; the Netherlands: b = 0.0002; t (1682) = 1.87; p = .061). The interaction of performance Year 1 and time Year 2 was significant in Germany but not the other two countries (Germany: b = −0.012; t (4082) = −3.88; p < .001; Uruguay: b = 0.007; t (343) = 0.59; p = .550; the Netherlands: b = −0.001; t (1682) = −1.16; p = .243), with a positive effect of more study time for all students, but an increased effect of more study time in year 2 for low-performing students compared to high-performing students. This result was further explored with a quintile split as in analysis 2 (see below). The interaction of time Year 2 and performance Year 2 on the effect of performance Year 3 was significant in Germany and the Netherlands but not Uruguay (Germany: b = 0.60; t (4082) = 5.42; p < .001; Uruguay: b = −1.02; t (343) = −1.29; p = .197; the Netherlands: b = 1.68; t (1682) = 3.79; p < .001), with a positive effect of study time in year 2 on the performance in year 3, but an increased effect of study time in year 2 on year 3 for high-performance students in year 2 compared to low-performance students in year 2. The three-way interaction was significant in Germany ( b = −.04; t (4082) = −2.70; p = .006), and the Netherlands ( b = −.03; t (1682) = −2.28; p = .022), but not in Uruguay ( b = .0005; t (343) = .005; p = .996; see Fig. ​ Fig.2). 2 ). The three-way interaction indicated that low-performing students of year 1 who spent a lot of time studying mathematics in year 2 and showed severe improvements in year 2 continued to perform at a high level in year 3. However, low-performing year 1 students who spent more time using the software in year 2, but did not improve in year 2, did not show high-performance scores in year 3. In contrast to low-performance students, high-performance students showed smaller effects of more high-quality study time in year 2. This result showed that not only study time, but study time and improving while studying—i.e., the quality while studying, improved performance scores—was most beneficial for low-performance students in year 1.

The two-way interaction of performance Year 1 and time Year 2 on performance Year 3 was further examined in an exploratory analysis (see Fig. ​ Fig.3). 3 ). As in analysis 2, we conducted a quintile split with respect to the performance in year 1 for Germany and the combined dataset for the other two countries, respectively. Results showed a significant interaction in Germany ( b = −.002; t (1632) = −3.38; p < .001) and the combined dataset ( b = −.0003; t (813) = −1.97; p = .048) with more study time in year 2 leading to increased performance scores in year 3; however, low-performing students in year 1 revealed a steeper increase in performance in the third year, with more study time, compared to high-performing students.

The aim of this study was to systematically investigate the effect of study time spent on solving mathematical problem sets on students’ achievements in mathematics. Data collected with an online educational software for mathematics was used to address this question. More than six thousand K-12 students who computed more than 1.1 million problem sets within three consecutive school years were analyzed. Results showed that (a) study time had a positive effect on mathematical achievement scores of K-12 students (age 9-16); (b) especially low-performing students enhanced their performance with increased study time; (c) performance increases persisted over time; and (d) the quality of study time influences the effect of study time on performance scores. These results contribute to previous findings on whether study time influences achievement gains in mathematics (Cheema and Sheridan, 2015 ; Cooper et al., 2006 ; Cooper and Valentine, 2001 ; Gortner-Lahmers and Zulauf, 2000 ; Jez and Wassmer, 2015 ; Louw et al., 2008 ; Macnamara et al., 2014 ; Plant et al., 2005 ; Schuman et al., 1985 ; Trautwein, 2007 ) and replicated the observation of relatively stable academic abilities over time of previous studies (Aunio and Niemivirta, 2010 ; Jordan et al., 2011 ; Siegler et al., 2012 ; Watts et al., 2014 ). On the methodological consideration, we add to these studies by (a) using precise study time measures instead of assessing study time with questionnaires; (b) investigating the effects over a considerably large time frame of three consecutive school years; and (c) analyzing a large dataset.

Results from this study extend previous studies on the influence of study time on academic achievement scores by investigating whether the effects of study time depended on students’ prior abilities. A significant interaction of an exploratory analysis of analysis 2 provided evidence that extra study time in year 2 (2018-2019) led to high gains in performance for those students with the lowest 20% performance scores in year 1, compared to those students with the highest 20% performance scores in year 1 4 . This interaction was further backed up with an analysis (analysis 3) which investigated the interaction of study time in year 2 and performance in year 1 on students’ performance in year 3 and showed that the low-performing students (bottom 20%) of year 1 who increased their study time in year 2 revealed steep performance gains with increasing study time compared to high-performance students (upper 20%) of year 1. Together, these results provide evidence of the positive effect of extra study time on students’ performance and that especially weak students may boost their performance in mathematics the most by increasing their study time.

This investigation did not address the question of whether cognitive abilities (Hilbert et al., 2019 ), motivational factors (Perels et al., 2009 ; Rosário et al., 2013 ), or effort (Flunger et al., 2015 ; Trautwein, 2007 ) determine academic achievement scores. However, without spending time to learn something, by any means, how should learning occur at all? In other words, without increasing the quantity of study time, qualitative factors, such as cognitive abilities, motivational factors, or any psychological process with an effect on learning, always must have a limited effect on performance scores in mathematics. Nevertheless, we investigated the influence of times’ quality. The finding of analysis 3 suggests that students with low abilities in the first year who spent more time in the second year studying, and improved while studying, revealed high-performance scores in the third year, compared to those students who increased their study time, but did not improve while studying. This result shows that students who improve while studying (i.e., high-quality study time) reveal long-lasting effects of their study time. However, we propose that increasing their study time was an essential condition for learning in the first place and that other factors such as improving while studying, self-regulatory skills, motivational factors, and effort bear upon the study time spent learning. In short, the first condition which needs to be met in learning is the investment of time.

One possible methodological improvement in this study is the measurement of study time. While most of the previous studies assessed study time with questionnaires, this investigation measured study time using the computer software. Computer logs of study time provide more precise measures and are not biased through students’ biases regarding self-monitoring. As self-regulatory skills are known to influence academic achievement scores, such biases may directly influence results from studies using self-assessments. For example, it may be that students with elevated self-regulatory skills estimate their study time differently compared to students with low self-regulatory skills. Moreover, studies that examined study time with questionnaires did not examine the precise measure of study time with problem sets but study time overall. This may consist of recapping the previous lecture or lectures and may consist of much more time involvement than the actual study time spent to compute problem sets. Therefore, the accumulated study time or homework time measured with questionnaires may comprise much more study activities than the computation time of problem sets. Here, we investigated the effect of study time on the performance of the exercises the study time was measured and the performance on exercises later on, with positive effects of extra study time on both time scale measures.

The results of the present study are limited in several ways. First, Dutch students spent the most time with the software and the effect of extra study time might be lower for children who already studied a lot. Second, the time students spent with other learning materials, in addition to the software, was unknown, as well as teachers’ instructional time on topics in school. Both factors may influence the effect of study time on students’ performance. For instance, the effect of study time with the software may differ between students who spent less time, compared to more time, with paper and pencil problem sets. Third, students’ performance was measured as the deviation of their results to the results of other students on the same problem set. However, it may be that teachers assigned hard problem sets, which were above their abilities and the general learning goals, specifically to their strong students. In such a scenario, and if the actual strong student would not be able to reach a high accuracy on these problem sets, an actually strong student would reveal a low-performance score. Even though such a scenario cannot be ruled out in this current investigation, it appears that it does not reflect teachers’ usual assignment policy. More plausibly, teachers assign problem sets to their students which meet their standards with the aim of achieving a learning goal. Fourth, it is unclear which factors influenced the quality of study time. Unfortunately, the dataset did not include psychological factors such as motivation, or self-regulation, nor did it include differences between the characteristics of problem sets.

These results may encourage poor performing students and their teachers to keep an eye upon engaging in mathematics and keep spending time to solve problem sets. High-school mathematics consists of comparably problems with clear solutions. In fact, all of these are solvable—in stark contrast to many math problems. The investment of time to seek out for the right answer is the first step to get it right.

Acknowledgements

We thank Bettermarks for sharing their data with us. We thank Kristin Manning for her enormous helpful comments on an earlier version of the manuscript.

Availability of data and material

Code availability.

All analyses will be available on https://osf.io/ .

Open Access funding enabled and organized by Projekt DEAL.

Declarations

The author declares no competing interests.

The data was provided to the author by Bettermarks. There is no affiliation between the company and the author of this manuscript. The opinions expressed in this publication are those of the author and do not necessarily reflect the views of Bettermarks.

1 After the data was obtained and analyzed, the completion rate of finished problem sets of the students included in the analyses was provided for each cohort, respectively. The German cohort completed 97% of their problem sets, the Uruguayan cohort completed 94% of their problem sets, and the Dutch cohort completed 98% of their problem sets.

2 Please note that data of year 3 only considered problem sets computed between September 1st, until March 1st, due to the COVID-19 outbreak and the subsequent shutdown of schools.

3 The datasets were combined to keep the power high for this analysis.

4 Please note that this interaction was observed in the German dataset while the result of the other analysis that included the Uruguayan and Dutch students revealed a trend of this effect.

Current themes of research:

I seek to investigate factors that influence students’ decision to leave a current task or in reverse factors that keep students attracted with a current task (e.g., studying mathematics). On the search factors that drive students’ decision to stick to the current task, I currently examine the optimal difficulty level (not too easy and not too difficult) at which students stick to the current task. While most of my research will be based on laboratory studies, some questions will be addressed with the large dataset examined in this study. The overall aim is to build open source close loop recommender system that is publicly available that provides students with problem sets of optimal difficulty so that students stay encouraged to learn. This study serves as the baseline project to show that increasing students’ study time leads to increased performance scores in the longer run.

Most relevant publications in the field of Psychology of Education:

No previous publications.

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

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Too Much Homework Can Lower Test Scores, Researchers Say

By: Natalie Wolchover Published: 03/30/2012 09:42 AM EDT on Lifes Little Mysteries

Piling on the homework doesn't help kids do better in school. In fact, it can lower their test scores.

That's the conclusion of a group of Australian researchers, who have taken the aggregate results of several recent studies investigating the relationship between time spent on homework and students' academic performance.

According to Richard Walker, an educational psychologist at Sydney University, data shows that in countries where more time is spent on homework, students score lower on a standardized test called the Program for International Student Assessment, or PISA. The same correlation is also seen when comparing homework time and test performance at schools within countries. Past studies have also demonstrated this basic trend.

Inundating children with hours of homework each night is detrimental, the research suggests, while an hour or two per week usually doesn't impact test scores one way or the other. However, homework only bolsters students' academic performance during their last three years of grade school. "There is little benefit for most students until senior high school (grades 10-12)," Walker told Life's Little Mysteries .

The research is detailed in his new book, "Reforming Homework: Practices, Learning and Policies" (Palgrave Macmillan, 2012).

The same basic finding holds true across the globe, including in the U.S., according to Gerald LeTendre of Pennsylvania State University. He and his colleagues have found that teachers typically give take-home assignments that are unhelpful busy work. Assigning homework "appeared to be a remedial strategy (a consequence of not covering topics in class, exercises for students struggling, a way to supplement poor quality educational settings), and not an advancement strategy (work designed to accelerate, improve or get students to excel)," LeTendre wrote in an email. [ Kids Believe Literally Everything They Read Online, Even Tree Octopuses ]

This type of remedial homework tends to produce marginally lower test scores compared with children who are not given the work. Even the helpful, advancing kind of assignments ought to be limited; Harris Cooper, a professor of education at Duke University, has recommended that students be given no more than 10 to 15 minutes of homework per night in second grade, with an increase of no more than 10 to 15 minutes in each successive year.

Most homework's neutral or negative impact on students' academic performance implies there are better ways for them to spend their after school hours than completing worksheets. So, what should they be doing? According to LeTendre, learning to play a musical instrument or participating in clubs and sports all seem beneficial , but there's no one answer that applies to everyone.

"These after-school activities have much more diffuse goals than single subject test scores," he wrote. "When I talk to parents … they want their kids to be well-rounded, creative, happy individuals — not just kids who ace the tests."

Follow Natalie Wolchover on Twitter @nattyover . Follow Life's Little Mysteries on Twitter @llmysteries , then join us on Facebook .

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Copyright 2012 Lifes Little Mysteries, a TechMediaNetwork company. All rights reserved. This material may not be published, broadcast, rewritten or redistributed.

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Harvard and Caltech Will Require Test Scores for Admission

The universities are the latest highly selective schools to end their policies that made submitting SAT or ACT scores optional.

By Anemona Hartocollis and Stephanie Saul

Harvard will reinstate standardized testing as a requirement of admission, the university announced Thursday, becoming the latest in a series of highly competitive universities to reverse their test-optional policies.

Students applying to enter Harvard in fall 2025 and beyond will be required to submit SAT or ACT scores, though the university said a few other test scores will be accepted in “exceptional cases,” including Advanced Placement or International Baccalaureate tests. The university had previously said it was going to keep its test-optional policy through the entering class of fall 2026.

Within hours of Harvard’s announcement, Caltech, a science and engineering institute, also said it was reinstating its testing requirements for students applying for admission in fall 2025.

The schools had been among nearly 2,000 colleges across the country that dropped test score requirements over the last few years, a trend that escalated during the pandemic when it was harder for students to get to test sites.

Dropping test score requirements was widely viewed as a tool to help diversify admissions, by encouraging poor and underrepresented students who had potential but did not score well on the tests to apply. But supporters of the tests have said without scores, it became harder to identify promising students who outperformed in their environments.

In explaining its decision to accelerate the return to testing, Harvard cited a study by Opportunity Insights , which found that test scores were a better predictor of academic success in college than high school grades and that they can help admissions officers identify highly talented students from low income groups who might otherwise had gone unnoticed.

“Standardized tests are a means for all students, regardless of their background and life experience, to provide information that is predictive of success in college and beyond,” Hopi Hoekstra, dean of the faculty of arts and sciences, said in a statement announcing the move.

“In short, more information, especially such strongly predictive information, is valuable for identifying talent from across the socioeconomic range,” she added.

Caltech, in Pasadena, Calif., said that reinstating testing requirements reaffirmed the school’s “commitment as a community of scientists and engineers to using all relevant data in its decision-making processes.”

Harvard and Caltech join a growing number of schools, notable for their selectivity, that have since reversed their policies, including Brown, Yale, Dartmouth, M.I.T., Georgetown, Purdue and the University of Texas at Austin.

For Harvard, the move comes at a time of transition, and perhaps a return to more conservative policies.

Last June, the Supreme Court struck down race-conscious college admissions in cases involving Harvard and the University of North Carolina, raising fears that with the demise of affirmative action, those schools would become less diverse.

And in January, Harvard’s first Black president, Claudine Gay, resigned under pressure from critics who said she had not acted strongly enough to combat antisemitism on campus after the Oct. 7 attack by Hamas on Israel, and under mounting accusations of plagiarism in her academic work, which she stood by.

The provost, Alan Garber, was named interim president, while the dean of the law school, John Manning, became interim provost, the university’s second-highest administrative position. Mr. Manning is considered a strong potential candidate to replace Dr. Gay. His background stands out for his conservative associations, having clerked for the former Supreme Court justice Antonin Scalia.

In the current climate on campus, a return to test scores could be seen as a return to tradition. It also may address concerns of many parents that the college admissions process, especially in elite institutions, is inscrutable and disconnected from merit.

Applications to Harvard were down by 5 percent this year, while those at many of its peer universities went up, suggesting that the recent turmoil may have dented its reputation. But it still received a staggering number of undergraduate applications — 54,008 — and admitted only 3.6 percent. Requiring test scores could make sorting through applications more manageable.

Critics of standardized tests have long raised concerns that the tests helped fuel inequality because some wealthier students raised their scores through high-priced tutoring. But recent studies have found that test scores help predict college grades, chances of graduation and post-college success, and that test scores are more reliable than high school grades, partly because of grade inflation in recent years .

But Robert Schaeffer, director of public education at FairTest, an organization that opposes standardized testing, said Thursday that the Opportunity Insights analysis had been criticized by other researchers. “Those scholars say that when you eliminate the role of wealth, test scores are not better than high school G.P.A.,” he said, adding that it is not clear whether that pattern is true among the admissions pool at super selective colleges such as Harvard.

Mr. Schaeffer said that at least 1,850 universities remain test optional, including Michigan, Vanderbilt, Wisconsin and Syracuse, which have recently extended their policies. “The vast majority of colleges will not require test scores.” An exception, he said, could be the University of North Carolina system, which is considering a plan to require tests, but only for those students with a G.P.A. below 2.8.

Acknowledging the concerns of critics, Harvard said that it would reassess the new policy regularly. The school said that test scores would be considered along with other information about an applicant’s experience, skills, talents, contributions to communities and references. They will also be looked at in the context of how other students are doing at the same high school.

“Admissions officers understand that not all students attend well-resourced schools, and those who come from modest economic backgrounds or first-generation college families may have had fewer opportunities to prepare for standardized tests,” William R. Fitzsimmons, Harvard’s dean of admissions and financial aid, said in a statement.

Harvard said that in the interest of selecting a diverse student body, it has enhanced financial aid and stepped up recruitment of underserved students by joining a consortium of 30 public and private universities that recruits students from rural communities.

An earlier version of this article misstated Robert Schaeffer’s position. He is the director of public education at FairTest, not the director.

How we handle corrections

Anemona Hartocollis is a national reporter for The Times, covering higher education. More about Anemona Hartocollis

Stephanie Saul reports on colleges and universities, with a recent focus on the dramatic changes in college admissions and the debate around diversity, equity and inclusion in higher education. More about Stephanie Saul

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Harvard announces return to required testing

Leading researchers cite strong evidence that testing expands opportunity

Students applying to Harvard College for fall 2025 admission will be required to submit standardized test scores, the Faculty of Arts and Sciences announced on Thursday. This new policy will be applied to the Class of 2029 admissions cycle and will be formally assessed at regular intervals.

For the Class of 2029 admissions cycle, Harvard will require submission of scores for the SAT or ACT. In exceptional cases in which applicants are unable to access SAT or ACT testing, other eligible tests will be accepted.

In a message to the FAS community on Thursday, Edgerley Family Dean of the Faculty of Arts and Sciences Hopi Hoekstra foregrounded “a number of factors” that underscored the decision.

“Standardized tests are a means for all students, regardless of their background and life experience, to provide information that is predictive of success in college and beyond,” she said. “Indeed, when students have the option of not submitting their test scores, they may choose to withhold information that, when interpreted by the admissions committee in the context of the local norms of their school, could have potentially helped their application. In short, more information, especially such strongly predictive information, is valuable for identifying talent from across the socioeconomic range.”

In research published last year, Harvard Professors Raj Chetty and David J. Deming and co-author John N. Friedman used data from more than 400 institutions and about 3.5 million undergrads per year to better understand socioeconomic diversity and admissions. Standardized tests emerged as an important tool to identify promising students at less-well-resourced high schools, particularly when paired with other academic credentials.

“Critics correctly note that standardized tests are not an unbiased measure of students’ qualifications, as students from higher-income families often have greater access to test prep and other resources,” said Chetty, the William A. Ackman Professor of Public Economics and director of Opportunity Insights . “But the data reveal that other measures — recommendation letters, extracurriculars, essays — are even more prone to such biases. Considering standardized test scores is likely to make the admissions process at Harvard more meritocratic while increasing socioeconomic diversity.”

Deming, the Kennedy School’s Isabelle and Scott Black Professor of Political Economy and a professor of education and economics at the Ed School, pointed to access as a key issue.

“The virtue of standardized tests is their universality,” he said. “Not everyone can hire an expensive college coach to help them craft a personal essay. But everyone has the chance to ace the SAT or the ACT. While some barriers do exist, the widespread availability of the test provides, in my view, the fairest admissions policy for disadvantaged applicants.”

In June 2020, as the pandemic severely limited access to standardized testing, Harvard began a test-optional policy under which students could apply to the College without submitting scores. The admissions cycle for the Class of 2028 was the fourth for which students were able to apply without submitting test scores. However, admissions has welcomed applicants to submit test scores, and the majority of those who matriculated during the past four years did so.

“Test scores can provide important information about a student’s application,” said William R. Fitzsimmons, dean of admissions and financial aid. “However, they representonly one factor among many as our admissions committee considers the whole person in making its decisions. Admissions officers understand that not all students attend well-resourced schools, and those who come from modest economic backgrounds or first-generation college families may have had fewer opportunities to prepare for standardized tests.”

In recent years, nonprofits such as Khan Academy have offered robust test-prep tools at no charge. In her message, Hoekstra said that access to testing should never prevent a student from applying to Harvard, and included information for those who may not be able to access the SAT or ACT, as well as tools such as Schoolhouse.world and other sources for no-cost tutoring and no-cost test preparation.

“We recognize that in parts of the United States there may be fewer students than in the past taking SAT or ACT for their state universities — and international applicants can also face barriers to testing,” said Joy St. John, director of admissions. “We hope that promising students faced with such challenges will still apply, using alternative forms of testing.”

Said Hoekstra: “Fundamentally, we know that talent is universal, but opportunity is not. With this change, we hope to strengthen our ability to identify these promising students, and to give Harvard the opportunity to support their development as thinkers and leaders who will contribute to shaping our world.”

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Return to Required Testing

• Publication date April 11, 2024
• Categories: Messages from the Dean , News

Dear FAS community,   Colleges and universities across the country paused the requirement of standardized test scores at the start of the COVID-19 pandemic when students no longer had reliable access to testing sites. As testing again became available, Harvard continued to use standardized test scores as an optional part of the admissions application, with the guidance that this practice was expected to continue through the admissions cycle for the Class of 2030. I write to announce that, starting with next year’s admissions cycle, Harvard College will require the submission of standardized test scores. The College will accept the SAT or ACT to meet the standardized test requirement. In exceptional cases in which those tests are not accessible, a set of alternative standardized tests can meet the requirement. More information is available on the website of the  Harvard College Admissions and Financial Aid Office .  

This decision to return to requiring testing was motivated by a number of factors. Standardized tests are a means for all students, regardless of their background and life experience, to provide information that is predictive of success in college and beyond. Indeed, when students have the option of not submitting their test scores, they may choose to withhold information that, when interpreted by the admissions committee in the context of the local norms of their school, could have potentially helped their application. In short, more information, especially such strongly predictive information, is valuable for identifying talent from across the socioeconomic range. 

 It is important to remember that – through Harvard’s whole-person admissions process – test scores are considered carefully with the expertise of the admissions committee alongside a plethora of information about an applicant’s experiences, skills, talents, and contributions to their communities, as well as their academic qualifications in relation to the norms of the applicant’s high school.     Reinstating this requirement brings important information back into the admissions process. That said, we recognize that this requirement also brings certain challenges. Access to testing should never prevent a student from applying to Harvard. In addition to providing alternative test options for those who cannot access the SAT or ACT, Harvard College Admissions provides information on  sources for no-cost tutoring and no-cost test preparation . And through Harvard’s need-based financial aid program, the ability to pay should also never prevent an applicant from saying “yes” to Harvard.   Through the admissions process, we seek to recruit students from all parts of our nation and across the world, from many walks of life, to bring with them to Harvard a universe of new questions, perspectives, and hopes for the future. Fundamentally, we know that talent is universal, but opportunity is not. With this change, we hope to strengthen our ability to identify these promising students and to give Harvard the opportunity to support their development as thinkers and leaders who will contribute to shaping our world.   Sincerely, Hopi Hoekstra

For more information, please see this  Harvard Gazette article .

Hopi Hoekstra Edgerley Family Dean of the Faculty of Arts and Sciences C. Y. Chan Professor of Arts and Sciences Xiaomeng Tong and Yu Chen Professor of Life Sciences