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Developing Critical Thinking in Physics: The Apprenticeship of Critique (Contributions from Science Education Research Book 7) 1st ed. 2020 Edition, Kindle Edition

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Laurence Viennot is Professor Emeritus of Physics at the University of Paris, in the Laboratory of Matter and Complex Systems. After a few years of research in astrophysics, she turned to the didactics of physics, of which she is one of the pioneers at the international level. She was a member of the first board of European Science Education Research Association. Among her research themes, common reasoning in physics and the development and evaluation of teaching sequences in physics occupy a major place. She has received two international medals (IUPAPE and GIREP). Her current research focuses on the development of critical thinking in physics students.

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Conceptual Development and Critical Attitude in Physics Education: A Pathway in the Search for Coherence

• First Online: 20 February 2019

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In recent years, the need to attract students towards physics has largely contributed to shape the objectives ascribed to physics teaching in many countries. Among these objectives, critical thinking is unanimously presented as of central importance. But at the same time a stress on competences jointly with this trend to simplify physics might lead to an underdevelopment of conceptual understanding. The following question then arises: can critical thinking be fostered in students without conceptual structuring and (still more importantly) without stressing the pivotal role of a search for coherence in science? This chapter briefly summarises some recent research on the joint development of a conceptual understanding and critical position among university students. In characterising students’ responses when confronted to various explanations of a physical phenomenon, these studies bring to bear conceptual markers as well as meta-cognitive, affective and critical indicators. Some profiles of co-development are characterised, including “delayed critique” and “expert anaesthesia of judgment”. The results strongly suggest that to disregard the objective of conceptual structuring is counterproductive for the development of students’ critical attitude. Through these exploratory studies, it appears that the conditions in which students can begin to search for coherence—whether in pursuit of conceptual understanding or to activate their critical potential—constitute a crucial objective for further research.

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Viennot, L. (2019). Conceptual Development and Critical Attitude in Physics Education: A Pathway in the Search for Coherence. In: Pietrocola, M. (eds) Upgrading Physics Education to Meet the Needs of Society. Springer, Cham. https://doi.org/10.1007/978-3-319-96163-7_13

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Physics Lab Inventory of Critical thinking

What is the plic.

The Physics Lab Inventory of Critical thinking (PLIC) is a closed-response survey designed to assess how students critically evaluate experimental methods, data, and models. We define critical thinking as the ways in which you make decisions about what to do and what to trust. In a scientific context, this decision-making is based in evidence that includes data, models, analyses, prior literature, etc.

Want to try out the PLIC? Please click here to access the "expert" version of the survey!

Interested in using the PLIC? Please click here  to access the course information survey!

Need to edit your start/end dates for the survey? Visit this form .

Design and Validation of the PLIC

The original conception of the PLIC came from analysis of student decision-making and reasoning in lab notes [ 1] : how well they interpreted data, whether they attempted to improve their experiments, and whether they identified and explained disagreements between data and models. To facilitate broad assessment (rather than painstaking analysis of lab notes), we create a context-rich, closed-response assessment. The PLIC context focuses on two groups completing a mass on a spring experiment to test the relationship between the period of oscillation and mass on the spring. The PLIC poses questions asking students to: a) interpret and evaluate the sample data, b) evaluate the methods, and c) suggest what the group should do next. From a free-response version, we collected common student responses and aggregated them into a closed response version. The questions include a mix of single-option Likert-scale questions (e.g. How well did the group's method evaluate the model?) and choose-many explanation questions (e.g. Which of the following best support your reasoning?). Students are limited to no more than three options for each 'choose-many' question. 

Responses were collected from over 50 expert physicists at multiple institutions. These responses were used to improve the assessment and to generate the scoring scheme. Students' scores, therefore, are related to how closely they respond to what experts say. Details of the scoring scheme will be included on this site soon.

Administering the PLIC

We have set up an automated system for signing up and administering the PLIC, based on work [ 2] by Lewandowski Group at the University of Colorado-Boulder. Any instructor interested in using the PLIC should follow the steps below.

1. To get started, instructors should fill out the Course Information Survey (CIS) available here . The survey includes questions about the course, instructor contact information, when the instructor would like the pre- and post-surveys to close.

2. The instructor is sent an email containing a link to the pre-instruction survey, which should be shared with students by the instructor whenever and however they would like.

3. Four days before the pre-survey is set to close, the instructor is sent an email reminder letting them know how many students have completed the pre-survey. If no one has filled it out at that point, the survey deadline is extended by 3 days.

4. Two days before the post-survey is set to open, the instructor is sent an email informing them that the post-survey link is on its way.

5. Two weeks before the post-survey is set to close, the instructor is sent an email containing a link to the post-instruction survey, which should be again shared with students by the instructor.

6. Four days before the post-survey is set to close, the instructor is sent an email reminder letting them know how many students have completed the post-survey. If no one has filled it out at that point, the survey deadline is extended by 3 days.

7. After the post-survey closes, the instructor is sent a report email including the names of students who completed the survey and a summary of their class’s performance.

Bonus: Instructors are able to change the date that they would like a survey (either pre or post) to close by completing a separate course date change form available here .

Publications

1 Holmes, N. G., Wieman, C. E., & Bonn, D. A. (2015). Teaching critical thinking. PNAS , 112 (36), 11199–11204. https://doi.org/10.1073/pnas.1505329112

2 Wilcox, B. R., Zwickl, B. M., Hobbs, R. D., Aiken, J. M., Welch, N. M., & Lewandowski, H. J. (2016). Alternative model for administration and analysis of research-based assessments. Physical Review Physics Education Research , 12 (1), 010139. https://doi.org/10.1103/PhysRevPhysEducRes.12.010139

Walsh, C., Quinn, K. N., Wieman, C., & Holmes, N. G. (2019). Quantifying critical thinking: Development and validation of the physics lab inventory of critical thinking. Physical Review Physics Education Research, 15(1), 010135. https://doi.org/10.1103/PhysRevPhysEducRes.15.010135

Quinn, K. N., Wieman, C. E., & Holmes, N. G. (2018). Interview Validation of the Physics Lab Inventory of Critical thinking (PLIC). In 2017 Physics Education Research Conference Proceedings (pp. 324–327). American Association of Physics Teachers. https://doi.org/10.1119/perc.2017.pr.076

Holmes, N. G., & Wieman, C. E. (2016). Preliminary development and validation of a diagnostic of critical thinking for introductory physics labs. In  2016 Physics Education Research Conference Proceedings  (pp. 156–159). American Association of Physics Teachers. https://doi.org/10.1119/perc.2016.pr.034

Holmes, N. G., & Wieman, C. E. (2015). Assessing modeling in the lab: Uncertainty and measurement. In M. Eblen-Zayas, E. Behringer, & J. Kozminski (Eds.),  2015 Conference on Laboratory Instruction Beyond the First Year of College  (pp. 44–47). College Park, MD. https://doi.org/10.1119/bfy.2015.pr.011

Holmes, N. G., Olsen, J., Thomas, J. L., & Wieman, C. E. (2017). Value added or misattributed? A multi-institution study on the educational benefit of labs for reinforcing physics content. Physical Review Physics Education Research , 13 (1), 010129. https://doi.org/10.1103/PhysRevPhysEducRes.13.010129

Blane Baker, Ph.D. , is Professor of Physics at his alma mater, William Jewell College, in Liberty, Missouri, USA. He is co-chair of the Sigma Pi Sigma 2022 Physics Congress, and a member of the American Physical Society (APS), the American Association of Physics Teachers (AAPT), and the Society of Physics Students (SPS). Dr. Baker holds the Wallace A. Hilton Endowed Chair in Physics at William Jewell College and is the author of Science in the Arena: Explanations and Analyses of Performances and Phenomena in Sport (IOP Concise Physics), published in 2018.

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Higher-Level Thinking in Physics Education

Taxonomy and levels of learning and thinking, remembering, understanding, further notes on higher-level thinking, chapter 1: higher-level thinking and applications to physics teaching.

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Blane Baker, "Higher-Level Thinking and Applications to Physics Teaching", Critical Thinking in the Physics Curriculum, Blane Baker

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Development of the highest levels of cognitive thinking is contingent upon student engagement in activities that emphasize examining relationships, critiquing arguments, designing experiments, and building models. The levels of cognitive thinking are introduced here, along with examples and writing prompts for assignments. Particular attention is given to the highest levels of cognitive thinking: analyzing, evaluating, and creating.

Professional and hidden physicists rely on cognitive abilities that emphasize constructing knowledge, evaluating arguments, and developing new models that can be applied and tested. While practitioners are steeped in the habits of mind of higher-level thinking, many students in physics courses have not yet mastered these kinds of thinking skills. With intentional practice and repetition, however, such skills can be developed quite effectively at all levels of the physics curriculum.

To produce materials for use in classrooms, a general understanding of cognitive thinking is needed. For our work here, the levels of cognitive thinking (and recent modifications), as specified in Bloom's taxonomy, are appropriate and are described. Later, various techniques, exercises, and examples are presented for use throughout the physics curriculum. Emphasis is given to the highest levels of thinking—analyzing, evaluating, and creating. Instructors are encouraged to incorporate higher-level thinking activities into their classrooms and laboratories to prepare students for a complex and ever-evolving world.

Building higher-level thinking skills has wide implications for students’ personal enrichment and their career development. In a world in which information (and misinformation) must be critically evaluated, the ability to apply higher-level thinking is crucial for citizens in the 21st century. In addition, employment in the 21st century demands that workers possess higher-level thinking skills to thrive in fast-paced and everchanging workplaces. Students who develop these skills as part of their educational background are in high demand as workers and are prepared to participate in society as informed citizens.

The development of higher-level thinking as proposed in these chapters will focus primarily on qualitative solutions to problems with some emphasis on building numerical arguments. Many other contributors have written quantitative problems for the physics education community; thus, these kinds of examples are already widely available. Besides improving higher-level thinking, the exercises discussed here are designed to expand students’ communication skills.

For reference, we will be using higher-level thinking and critical thinking interchangeably throughout the writing here.

In the late 1940s and early 1950s, several conferences were organized by educators to provide structural foundations to learning. From those meetings, several handbooks were written on educational goals and objectives. Along with these handbooks, a hierarchical model was developed to classify educational learning objectives. This model became known as Bloom's taxonomy after Benjamin Bloom who chaired the committee of educators who developed it. The original knowledge-based version of Bloom's taxonomy consists of the following levels: knowledge, comprehension, application, analysis, synthesis, and evaluation.

In the more traditional application of Bloom's taxonomy, learning progresses linearly from one level to another. Learners first master the knowledge and then use it at higher and higher levels until they are able to evaluate information. Evaluation typically refers to the ability to make judgments about information, the validity of ideas, or the quality of work. Over time, educators have come to embrace a more fluid style of learning and thinking in which learners move between the various kinds of thinking. A newer version of Bloom's taxonomy was established in 2001; the levels of cognitive thinking include: remembering, understanding, applying, analyzing, evaluating, and creating ( Fig. 1.1 ).

Levels of cognitive thinking: remembering, understanding, applying, analyzing, evaluating, and creating.

One of the goals here is to encourage teachers to design learning activities that promote development of higher-level thinking in their courses. Assigning these kinds of questions and prompts ensures that students develop the skills necessary for success in the 21st century. Abilities to think broadly and to critique arguments are essential in a society characterized by change.

Following this chapter on background, general taxonomy, and examples, the remainder of the book addresses higher-level thinking throughout the undergraduate physics curriculum. Various chapters provide strategies for implementing higher-level thinking into the physics curriculum and suggest examples of assignments and projects. In some cases, critiques of student answers are discussed and grading rubrics are included.

Overview and language

The ability to recall information is referred to as remembering. Remembering in the physics curriculum often focuses on retaining information, such as physical concepts, theories, and laws. Once information is retained, it can be used to explain observations and phenomena and, ultimately, to create new models, experiments, or inventions. Thus, basic knowledge is often the foundation for developing higher-level thinking, such as understanding and applying.

In a more integrated approach to learning, the process of remembering is combined with other levels of thinking to solve problems. As knowledge of concepts, principles, and theories is gained, learners begin to use that knowledge even before it is completely retained. The act of applying knowledge before it is fully mastered reinforces remembrance.

Multiple levels of thinking can be combined to develop more sophisticated solutions to problems. For example, as knowledge is acquired, it is applied to familiar situations. As students gain experience in application, they begin to create new knowledge through developing new products or inventions.

The language of remembering typically uses the words: finding, naming, retrieving, describing, listing, and recognizing.

Describe Newton's laws of motion.

Name the fundamental element responsible for life on Earth.

List the three main methods of heat transfer.

What are the essential steps in charging a metal dome by electrical induction?

Name and describe the physics principle responsible for electric generators.

Describe acoustic resonance and give an example.

State the first law of thermodynamics.

Describe how total internal reflection occurs.

What is conservation of mechanical energy?

Name the conservation law that applies to all collisions.

The ability to explain ideas or concepts refers to understanding. At the understanding level, practitioners can relate information to others in meaningful ways and explain what is happening in various scenarios. Understanding often begins by learning how physics concepts and principles explain the blueness of the sky or how a telescope works. As students improve their skills, understanding principles can translate into applying, analyzing, evaluating, and creating.

As an example, suppose that someone were to give an explanation based on incorrect principles or maybe even non-scientific theories. A student skilled in remembering and understanding can dissect the argument (analyzing) and then critique its merits (evaluating). Once evaluated, the argument is either logical (and, therefore, valid) or faulty. If a fallacy is found, skilled learners are able to propose alternative arguments that are reasonable and valid.

The language of understanding typically uses the key words: explaining, classifying, interpreting, summarizing, and paraphrasing.

Summarize the law of conservation of angular momentum.

Explain how a simple heat engine works and how its efficiency is determined.

What method of heat transfer is most important for an outside wall on a house? Explain.

Explain the concept of inertia for a body moving in deep space with no forces acting on it.

An observer notices that when a diver tucks, their angular speed increases. What principle describes this observation? Justify your answer.

Classify the forces acting on a block being pulled along a tabletop as field or contact forces.

In your own words, summarize Archimedes principle.

Paraphrase the work-kinetic energy theorem.

Classify nuclear collisions as elastic or inelastic and explain your reasoning.

Distinguish between infrared and visible electromagnetic waves.

Applying is characterized by the ability to utilize information (concepts, principles, and theories) in other familiar scenarios. Those who are competent in applying knowledge recognize what principles and concepts are important and employ that information in appropriate ways.

In the study of physics, applying knowledge often refers to using scientific equations to solve numerical problems. Numerical problem solving generally requires identifying given and unknown quantities, identifying the physics principles and equations needed, and devising methods for solution. Students often struggle with knowing what the problems are asking and what physics to apply. With practice, however, they can greatly improve their skills in numerical problem solving.

In other contexts, applying refers to using or implementing physics principles in familiar situations to address problems. Activities here focus on developing solutions or responses by incorporating knowledge and understanding of physics.

The language of applying typically includes key words, such as implementing, using, executing, and solving.

Using laws of motion, what causes a basketball to bounce as it strikes the ground?

A car traveling at 25.0 m/s begins braking so that the magnitude of its acceleration is 1.30 m/s 2 . Determine whether the car can come to a stop before striking a barrier 250.0 m directly in front of it.

The magnetic field at the center of a solenoid depends on the current as depicted by the data in Table 1.1 . From these data, find the magnetic field when the current is 4.0 A.

A ball of mass 0.20 kg is released from rest at a height of 1.5 m above the floor. After colliding with the floor, the ball bounces to a height of 1.2 m. Compare numerical values of the momentum before and after the collision.

A tank of water open to the atmosphere is filled to a height of 18.0 m relative to the bottom of the tank. Determine the speed of water exiting a small hole near the bottom of the tank.

Data showing current and magnetic field near the center of a solenoid.

Analyzing refers to breaking information into parts and determining how those parts contribute to our understanding. Analyzing also examines how quantities are related to one another and how those relationships contribute to knowledge.

Laboratory work in physics often focuses on dissecting data and looking for relationships between physical quantities. As relationships are established, models (and ultimately theories) are confirmed, modified, or developed as experiments demand. This ongoing process of examining relationships is central to the enterprise of science.

The process of analyzing naturally leads to making hypotheses and critiquing arguments, proposals, and designs. This level of thinking is referred to as evaluating and is critical for discerning whether or not a claim is valid. Given our constant inundation with claims and counterclaims, evaluating information and data is essential for an informed citizenry—not to mention practicing scientists and technical workers.

The language of analyzing usually includes key words, such as comparing, organizing, deconstructing, and interrogating.

While tuning a flute, a professional player extends the length of the instrument by 0.5 cm. Was the instrument sharp or flat when the flutist began the tuning process? How do you know? Give your reasoning.

Two pouches with the same shape and volume contain slightly different concentrations of salt as saline solutions. Container A has a higher salt concentration and is hung from height h, while Container B is hung from the same height. Compare the pressures in the bottoms of the two containers.

A siren from an emergency vehicle produces a frequency of 1150 Hz. When at rest near the side of the road, an observer hears a frequency of 1200 Hz coming from the vehicle and 5.0 s later, the perceived frequency is 1100 Hz. What happened during the 5.0 s interval? Include your reasoning.

As part of a strength and fitness program, a gymnast adds several kg of muscular mass to her arms and legs. Assess how this change affects rotational motions of the gymnast in the floor exercise where rotations in the air are integral to outstanding performances.

In a passive solar house incident radiation from the Sun passes through a transparent medium (glass) and strikes an inner wall, known as a Trombe wall. The Trombe wall has holes (slits) near the top and bottom and is made of thick concrete. Discuss why thick concrete is used and why slits are placed in the walls.

A public statue with a broad base has just begun to lean without falling. City officials hire you as a consultant and task you with providing an assessment. Your assessment must include the kind of monitoring needed for public safety and your reasoning.

Evaluating refers to critiquing information to develop solutions, make decisions, or justify courses of action or decisions. Scientists constantly evaluate data and information as they engage in scientific methods that emphasize hypothesizing and experimenting. Likewise, informed and engaged citizens vet data and information quite regularly.

One of the hallmarks of evaluating is the ability to examine arguments for flaws and/or gaps in logic. Flaws in arguments often lead to faulty designs and, in worst cases, disastrous effects. In my hometown of Kansas City, MO, a skywalk collapsed in 1981 due to changes in design that were not critiqued properly to discover their basic flaws. Evaluating also includes the validation of arguments to advance scientific and technical progress.

Evaluating data and information often leads thinkers to develop designs, models, and knowledge. In these cases, evaluating contributes to the highest level of thinking known as creating. Thus, multiple levels of thinking are pursued together in order to solve complex and demanding problems.

The language of evaluating typically uses the key words: checking, hypothesizing, critiquing, and experimenting.

Shipping experts responsible for operating a large ship realize that the waters in which they will be sailing are saltier than usual. To maintain the same water level on the side of the ship, these experts suggest decreasing the load of the ship. Evaluate whether or not their proposal is reasonable, starting with arguments that the waters in which they will be sailing are saltier than usual. Also, propose an alternative solution if the one suggested is flawed.

According to designers, a large inductive load in a circuit is causing significant impedance so that currents do not reach their desired values. Engineers propose to add an inductor in series with the rest of the circuit to solve the problem. Critique the engineers’ proposal and suggest an alternative solution if their solution is untenable.

When certain trucks pass over potholes in a road just before entering a bridge structure, the bridge is observed to bounce up and down more than usual. Hypothesize what is happening when these trucks pass over the potholes and move onto the bridge and give your reasoning.

An advocacy group for the oil industry claims that we cannot rely on solar energy because there is not enough solar energy reaching the Earth to satisfy humankind's demands. Critique their claims by making some basic assumptions about U.S. energy usage and comparing that to the amount of energy that we could expect to capture at the Earth's surface. Clearly state your conclusion.

A power supply (with variable voltage and current settings) is used to operate a red LED. However, when the power supply is used with green or blue LEDs, the devices do not operate (are not illuminated). Hypothesize why this occurs and discuss your reasoning.

Two superconducting circuits are arranged so that each has a straight section of wire that is parallel to a straight section in the other circuit. Propose two experimental ways to reduce forces between the parallel wires while keeping currents the same and estimate numerically how much these forces will be reduced in each of your scenarios.

An observer notices that a section of a train track buckled during the last heatwave. Propose a hypothesis to explain this effect and give your reasoning.

In the morning following a cold night, workers discover that a gas (fuel) storage tank has collapsed. Develop a hypothesis to explain the collapse and suggest an experiment to test your hypothesis.

Creating in the sciences usually refers to developing new models to describe nature or to devising new inventions or designs. Other distinguishing factors of creating may include designing novel experiments or advancing new theories.

One example of creating is proposing new models to explain nature or phenomena more accurately. Here, investigators might look at experimental data and propose several models. As more and more data are collected, working models are developed over time.

This highest level of thinking often is reserved for professionals working in the field, but not all work must be done within the academy. Novices can imagine new models, propose novel conceptual designs, and conceive of improvements that lead to inventions.

The language of creating typically uses the key words: designing, constructing, planning, producing, and inventing.

Propose a new product to add to new home construction to mitigate increasing temperatures due to climate change. What is unique about your solution? How would it help to lower temperatures? Discuss scientifically how your solution works.

One energy storage design consists of a rotating flywheel. Rotational energy in the form of 0.5 Iω 2 is developed for later use when devices, such as solar panels and wind turbines, are not producing due to intermittent sunshine or wind. After testing an original design, engineers find that a rotating disk needs to be re-designed due to space limitations. Propose a re-design of the disk so that it has the same moment of inertia but with a radius that is 50% of the original design.

A fence surrounding a farm field has a gate at one end. The gate is attached to a vertical post that, over time, has started to lean to one side due to the weight (and torque) produced by the gate. Propose a modification to the current design that helps prevent the problem described. Be sure to describe the modification and explain how your design addresses the problem.

A city has limited funds but wants to modify its street lights to prevent so much light from being projected upward. Their goals are to reduce light pollution and to re-direct as much light as possible so that most of the light shines on sidewalks and streets below. Propose a design that uses the current lights but addresses the problem of light pollution and re-directs light to traffic areas below. Be sure to describe the design and how it works.

During a natural disaster, 100 ml of medicine must be kept cold during transport from one city to another, about 150 km away. Design an insulated container from materials you might find in your home. Be sure to maximize the insulating properties of the vessel by considering convection, conduction, and radiation.

The human mind has evolved to engage in multiple kinds of thinking, but, broadly speaking, the brain makes decisions based on survival thinking and the more complex and nuanced evaluative thinking. Survival thinking refers to reacting to stimuli without carefully considering alternative actions. Decisions made using survival thinking are automatic with no time for reflection.

Critical (evaluative) thinking, by contrast, requires reflecting on what is known and what can be determined and then building arguments to formulate decisions or responses. Critical-thinking skills are much needed in a world where monumental problems threaten our way of life and existence. With intentional practice, critical-thinking skills can be developed throughout the physics curriculum. The physics classroom is an ideal learning ground for critical thinking given that physics as a discipline is steeped in rigorous critique of data and models.

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Physical Review Physics Education Research

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Quantifying critical thinking: Development and validation of the physics lab inventory of critical thinking

Cole walsh, katherine n. quinn, c. wieman, and n. g. holmes, phys. rev. phys. educ. res. 15 , 010135 – published 31 may 2019.

• Citing Articles (36)
• INTRODUCTION
• ASSESSMENT FRAMEWORK
• EARLY EVALUATIONS OF CONSTRUCT VALIDITY
• DEVELOPMENT OF CLOSED-RESPONSE FORMAT
• STATISTICAL RELIABILITY TESTING
• SUMMARY AND CONCLUSIONS
• ACKNOWLEDGMENTS

Introductory physics lab instruction is undergoing a transformation, with increasing emphasis on developing experimentation and critical thinking skills. These changes present a need for standardized assessment instruments to determine the degree to which students develop these skills through instructional labs. In this article, we present the development and validation of the physics lab inventory of critical thinking (PLIC). We define critical thinking as the ability to use data and evidence to decide what to trust and what to do. The PLIC is a 10-question, closed-response assessment that probes student critical thinking skills in the context of physics experimentation. Using interviews and data from 5584 students at 29 institutions, we demonstrate, through qualitative and quantitative means, the validity and reliability of the instrument at measuring student critical thinking skills. This establishes a valuable new assessment instrument for instructional labs.

• Received 21 January 2019

DOI: https://doi.org/10.1103/PhysRevPhysEducRes.15.010135

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

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• 1 Laboratory of Atomic and Solid State Physics, Cornell University, Ithaca, New York 14853, USA
• 2 Department of Physics and Graduate School of Education, Stanford University, Stanford, California 94305, USA
• * [email protected]

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Vol. 15, Iss. 1 — January - June 2019

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Distributions of respondents’ matched pre- and postscores on the PLIC ( N = 1911 ). The average score obtained by experts is marked with a black vertical line.

Average score (representing question difficulty) for each of the 10 PLIC questions. The average expected score that would be obtained through random guessing is marked with a black square. Scores on the first seven questions are statistically different between the pre- and postsurveys (Mann-Whitney U, Holm-Bonferroni corrected α < 0.05 ).

Boxplots comparing presurvey scores for students in FY and BFY labs, and experts. Horizontal lines indicate the lower and upper quartiles and the median score. Scores lying outside 1.5 × IQR (inter-quartile range) are indicated as outliers.

Boxplots of students’ total scores on the PLIC grouped by the type of lab students participated in. Horizontal lines indicate the lower and upper quartiles and the median score. Scores lying outside 1.5 × IQR are labeled as outliers.

Excerpt from page four of the PLIC describing the methods of the two hypothetical groups of students. The final multiple choice questions ask respondents which group they think did a better job of testing the model, while the multiple response question asks students to elaborate on their reasoning.

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Critical thinking skills assessment instrument in physics subjects: how to develop a four tier diagnostic test?

A A Waluyo 1 , Hartono 1 and Sulhadi 1

Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series , Volume 1918 , Physics and its Application Citation A A Waluyo et al 2021 J. Phys.: Conf. Ser. 1918 022011 DOI 10.1088/1742-6596/1918/2/022011

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1 Physics Education, Faculty of Mathematics and Natural Science, Universitas Negeri Semarang, Indonesia

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Critical thinking is a thinking skills that involves a process of reasoning and reflective thinking that cannot be directly observed, so it requires a separate assessment instrument. This research is a development research that aims to produce an instrument for assessing critical thinking skills that can measure students' critical thinking skills and ilustrate the interconnectedness between aspects of critical thinking skills. The sample was selected using random sampling technique of 109 students in the trial stages and 136 students in the implementation stages. Data analysis was performed through several test that is content validity, construct validity, reliability, the level of students' critical thinking skills, and analysis of variance. The validity test shows that the instrument contains 4 factors that match theorized and the content validity score shows that can be used. While the reliability test shows that the Cronbach Alpha coefficient of 0,820. The tier of critical thinking skills of high school students in Banyumas Regency is less. Analysis of the relationship aspects of critical thinking skills shows that each aspect of critical thinking skills are interconnected with the analysis aspect as the basic and the conclusion and evaluation aspects as the culmination of being mutually sustainable in producing solutions.

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MIT faculty, instructors, students experiment with generative AI in teaching and learning

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How can MIT’s community leverage generative AI to support learning and work on campus and beyond?

At MIT’s Festival of Learning 2024, faculty and instructors, students, staff, and alumni exchanged perspectives about the digital tools and innovations they’re experimenting with in the classroom. Panelists agreed that generative AI should be used to scaffold — not replace — learning experiences.

This annual event, co-sponsored by MIT Open Learning and the Office of the Vice Chancellor, celebrates teaching and learning innovations. When introducing new teaching and learning technologies, panelists stressed the importance of iteration and teaching students how to develop critical thinking skills while leveraging technologies like generative AI.

“The Festival of Learning brings the MIT community together to explore and celebrate what we do every day in the classroom,” said Christopher Capozzola, senior associate dean for open learning. “This year's deep dive into generative AI was reflective and practical — yet another remarkable instance of ‘mind and hand’ here at the Institute.”   

Incorporating generative AI into learning experiences 

MIT faculty and instructors aren’t just willing to experiment with generative AI — some believe it’s a necessary tool to prepare students to be competitive in the workforce. “In a future state, we will know how to teach skills with generative AI, but we need to be making iterative steps to get there instead of waiting around,” said Melissa Webster, lecturer in managerial communication at MIT Sloan School of Management. 

Some educators are revisiting their courses’ learning goals and redesigning assignments so students can achieve the desired outcomes in a world with AI. Webster, for example, previously paired written and oral assignments so students would develop ways of thinking. But, she saw an opportunity for teaching experimentation with generative AI. If students are using tools such as ChatGPT to help produce writing, Webster asked, “how do we still get the thinking part in there?”

One of the new assignments Webster developed asked students to generate cover letters through ChatGPT and critique the results from the perspective of future hiring managers. Beyond learning how to refine generative AI prompts to produce better outputs, Webster shared that “students are thinking more about their thinking.” Reviewing their ChatGPT-generated cover letter helped students determine what to say and how to say it, supporting their development of higher-level strategic skills like persuasion and understanding audiences.

Takako Aikawa, senior lecturer at the MIT Global Studies and Languages Section, redesigned a vocabulary exercise to ensure students developed a deeper understanding of the Japanese language, rather than just right or wrong answers. Students compared short sentences written by themselves and by ChatGPT and developed broader vocabulary and grammar patterns beyond the textbook. “This type of activity enhances not only their linguistic skills but stimulates their metacognitive or analytical thinking,” said Aikawa. “They have to think in Japanese for these exercises.”

While these panelists and other Institute faculty and instructors are redesigning their assignments, many MIT undergraduate and graduate students across different academic departments are leveraging generative AI for efficiency: creating presentations, summarizing notes, and quickly retrieving specific ideas from long documents. But this technology can also creatively personalize learning experiences. Its ability to communicate information in different ways allows students with different backgrounds and abilities to adapt course material in a way that’s specific to their particular context. 

Generative AI, for example, can help with student-centered learning at the K-12 level. Joe Diaz, program manager and STEAM educator for MIT pK-12 at Open Learning, encouraged educators to foster learning experiences where the student can take ownership. “Take something that kids care about and they’re passionate about, and they can discern where [generative AI] might not be correct or trustworthy,” said Diaz.

Panelists encouraged educators to think about generative AI in ways that move beyond a course policy statement. When incorporating generative AI into assignments, the key is to be clear about learning goals and open to sharing examples of how generative AI could be used in ways that align with those goals. 

The importance of critical thinking

Although generative AI can have positive impacts on educational experiences, users need to understand why large language models might produce incorrect or biased results. Faculty, instructors, and student panelists emphasized that it’s critical to contextualize how generative AI works. “[Instructors] try to explain what goes on in the back end and that really does help my understanding when reading the answers that I’m getting from ChatGPT or Copilot,” said Joyce Yuan, a senior in computer science. 

Jesse Thaler, professor of physics and director of the National Science Foundation Institute for Artificial Intelligence and Fundamental Interactions, warned about trusting a probabilistic tool to give definitive answers without uncertainty bands. “The interface and the output needs to be of a form that there are these pieces that you can verify or things that you can cross-check,” Thaler said.

When introducing tools like calculators or generative AI, the faculty and instructors on the panel said it’s essential for students to develop critical thinking skills in those particular academic and professional contexts. Computer science courses, for example, could permit students to use ChatGPT for help with their homework if the problem sets are broad enough that generative AI tools wouldn’t capture the full answer. However, introductory students who haven’t developed the understanding of programming concepts need to be able to discern whether the information ChatGPT generated was accurate or not.

Ana Bell, senior lecturer of the Department of Electrical Engineering and Computer Science and MITx digital learning scientist, dedicated one class toward the end of the semester of Course 6.100L (Introduction to Computer Science and Programming Using Python) to teach students how to use ChatGPT for programming questions. She wanted students to understand why setting up generative AI tools with the context for programming problems, inputting as many details as possible, will help achieve the best possible results. “Even after it gives you a response back, you have to be critical about that response,” said Bell. By waiting to introduce ChatGPT until this stage, students were able to look at generative AI’s answers critically because they had spent the semester developing the skills to be able to identify whether problem sets were incorrect or might not work for every case. 

A scaffold for learning experiences

The bottom line from the panelists during the Festival of Learning was that generative AI should provide scaffolding for engaging learning experiences where students can still achieve desired learning goals. The MIT undergraduate and graduate student panelists found it invaluable when educators set expectations for the course about when and how it’s appropriate to use AI tools. Informing students of the learning goals allows them to understand whether generative AI will help or hinder their learning. Student panelists asked for trust that they would use generative AI as a starting point, or treat it like a brainstorming session with a friend for a group project. Faculty and instructor panelists said they will continue iterating their lesson plans to best support student learning and critical thinking. 

Panelists from both sides of the classroom discussed the importance of generative AI users being responsible for the content they produce and avoiding automation bias — trusting the technology’s response implicitly without thinking critically about why it produced that answer and whether it’s accurate. But since generative AI is built by people making design decisions, Thaler told students, “You have power to change the behavior of those tools.”

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MIT faculty, instructors, students experiment with generative AI in teaching and learning

How can MIT’s community leverage generative AI to support learning and work on campus and beyond?

At MIT’s Festival of Learning 2024, faculty and instructors, students, staff, and alumni exchanged perspectives about the digital tools and innovations they’re experimenting with in the classroom. Panelists agreed that generative AI should be used to scaffold — not replace — learning experiences.

This annual event, co-sponsored by MIT Open Learning and the Office of the Vice Chancellor, celebrates teaching and learning innovations. When introducing new teaching and learning technologies, panelists stressed the importance of iteration and teaching students how to develop critical thinking skills while leveraging technologies like generative AI.

“The Festival of Learning brings the MIT community together to explore and celebrate what we do every day in the classroom,” said Christopher Capozzola, senior associate dean for open learning. “This year's deep dive into generative AI was reflective and practical — yet another remarkable instance of ‘mind and hand’ here at the Institute.”   

Incorporating generative AI into learning experiences 

MIT faculty and instructors aren’t just willing to experiment with generative AI — some believe it’s a necessary tool to prepare students to be competitive in the workforce. “In a future state, we will know how to teach skills with generative AI, but we need to be making iterative steps to get there instead of waiting around,” said Melissa Webster, lecturer in managerial communication at MIT Sloan School of Management. 

Some educators are revisiting their courses’ learning goals and redesigning assignments so students can achieve the desired outcomes in a world with AI. Webster, for example, previously paired written and oral assignments so students would develop ways of thinking. But, she saw an opportunity for teaching experimentation with generative AI. If students are using tools such as ChatGPT to help produce writing, Webster asked, “how do we still get the thinking part in there?”

One of the new assignments Webster developed asked students to generate cover letters through ChatGPT and critique the results from the perspective of future hiring managers. Beyond learning how to refine generative AI prompts to produce better outputs, Webster shared that “students are thinking more about their thinking.” Reviewing their ChatGPT-generated cover letter helped students determine what to say and how to say it, supporting their development of higher-level strategic skills like persuasion and understanding audiences.

Takako Aikawa, senior lecturer at the MIT Global Studies and Languages Section, redesigned a vocabulary exercise to ensure students developed a deeper understanding of the Japanese language, rather than just right or wrong answers. Students compared short sentences written by themselves and by ChatGPT and developed broader vocabulary and grammar patterns beyond the textbook. “This type of activity enhances not only their linguistic skills but stimulates their metacognitive or analytical thinking,” said Aikawa. “They have to think in Japanese for these exercises.”

While these panelists and other Institute faculty and instructors are redesigning their assignments, many MIT undergraduate and graduate students across different academic departments are leveraging generative AI for efficiency: creating presentations, summarizing notes, and quickly retrieving specific ideas from long documents. But this technology can also creatively personalize learning experiences. Its ability to communicate information in different ways allows students with different backgrounds and abilities to adapt course material in a way that’s specific to their particular context. 

Generative AI, for example, can help with student-centered learning at the K-12 level. Joe Diaz, program manager and STEAM educator for MIT pK-12 at Open Learning, encouraged educators to foster learning experiences where the student can take ownership. “Take something that kids care about and they’re passionate about, and they can discern where [generative AI] might not be correct or trustworthy,” said Diaz.

Panelists encouraged educators to think about generative AI in ways that move beyond a course policy statement. When incorporating generative AI into assignments, the key is to be clear about learning goals and open to sharing examples of how generative AI could be used in ways that align with those goals. 

The importance of critical thinking

Although generative AI can have positive impacts on educational experiences, users need to understand why large language models might produce incorrect or biased results. Faculty, instructors, and student panelists emphasized that it’s critical to contextualize how generative AI works. “[Instructors] try to explain what goes on in the back end and that really does help my understanding when reading the answers that I’m getting from ChatGPT or Copilot,” said Joyce Yuan, a senior in computer science. 

Jesse Thaler, professor of physics and director of the National Science Foundation Institute for Artificial Intelligence and Fundamental Interactions, warned about trusting a probabilistic tool to give definitive answers without uncertainty bands. “The interface and the output needs to be of a form that there are these pieces that you can verify or things that you can cross-check,” Thaler said.

When introducing tools like calculators or generative AI, the faculty and instructors on the panel said it’s essential for students to develop critical thinking skills in those particular academic and professional contexts. Computer science courses, for example, could permit students to use ChatGPT for help with their homework if the problem sets are broad enough that generative AI tools wouldn’t capture the full answer. However, introductory students who haven’t developed the understanding of programming concepts need to be able to discern whether the information ChatGPT generated was accurate or not.

Ana Bell, senior lecturer of the Department of Electrical Engineering and Computer Science and MITx digital learning scientist, dedicated one class toward the end of the semester of Course 6.100L (Introduction to Computer Science and Programming Using Python) to teach students how to use ChatGPT for programming questions. She wanted students to understand why setting up generative AI tools with the context for programming problems, inputting as many details as possible, will help achieve the best possible results. “Even after it gives you a response back, you have to be critical about that response,” said Bell. By waiting to introduce ChatGPT until this stage, students were able to look at generative AI’s answers critically because they had spent the semester developing the skills to be able to identify whether problem sets were incorrect or might not work for every case. 

A scaffold for learning experiences

The bottom line from the panelists during the Festival of Learning was that generative AI should provide scaffolding for engaging learning experiences where students can still achieve desired learning goals. The MIT undergraduate and graduate student panelists found it invaluable when educators set expectations for the course about when and how it’s appropriate to use AI tools. Informing students of the learning goals allows them to understand whether generative AI will help or hinder their learning. Student panelists asked for trust that they would use generative AI as a starting point, or treat it like a brainstorming session with a friend for a group project. Faculty and instructor panelists said they will continue iterating their lesson plans to best support student learning and critical thinking. 

Panelists from both sides of the classroom discussed the importance of generative AI users being responsible for the content they produce and avoiding automation bias — trusting the technology’s response implicitly without thinking critically about why it produced that answer and whether it’s accurate. But since generative AI is built by people making design decisions, Thaler told students, “You have power to change the behavior of those tools.”

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15 Fun Decision Making Games for Kids

1. Online Decision Making Games 

3. connect four, 5. ticket to ride: first journey, 6. catan junior, 9. battleship, 10. guess who.

Making decisions is a big part of growing up. Learning to make good decisions early on is super important for kids. It helps them become more independent, confident, and ready to face the world. That’s where decision making games for kids come into play. These games teach kids how to think ahead, make choices, and understand what happens because of those choices—all while having a blast!

SplashLearn: Most Comprehensive Learning Program for PreK-5

SplashLearn inspires lifelong curiosity with its game-based PreK-5 learning program loved by over 40 million children. With over 4,000 fun games and activities, it’s the perfect balance of learning and play for your little one.

In this blog, we’re going to dive into some fantastic games that do just that. From classic board games that have been around for years to new card games that will soon become favorites, we’ve got a list that will help any kid become a decision-making champ. 

Best for Which Ages: 3 years and up

Decision making games online are one of the best choice making activities for kids to sharpen their critical thinking, problem-solving, and strategic planning skills in a fun, interactive environment. Engaging with these games teaches children to make quick decisions, analyze outcomes, and adapt their strategies in real time. Here’s a look at some engaging online decision making games that are perfect for young minds:

• Challenge Two of a Kind Game

This game tests memory and attention to detail as players flip cards to find matching pairs. It’s about remembering what you saw and making strategic decisions on which cards to flip next. Perfect for developing concentration and memory recall, it’s a hit among kids looking to challenge their minds.

• Play Jumble Mania Game

Jumble Mania sharpens spelling and vocabulary by challenging players to rearrange jumbled letters to form words. This game enhances decision making by requiring players to choose the most logical order of letters, improving their language skills and quick thinking in a fun, engaging way.

• Challenge Match-Up Puzzles Game

Match-up puzzles take the challenge up by mixing memory skills with problem-solving. Players must match related items, not just identical ones, adding an extra layer of decision making. This game is excellent for kids who enjoy puzzles and are ready to think outside the box.

Best for Which Age: 3 years and up

Go Fish is a card game that sharpens memory and introduces kids to strategic thinking. Players ask each other for cards to make sets, using strategy to remember who holds which cards.

How to Play:

• Deal five cards to each player and place the rest in a “fish pond” in the center.
• Players ask others for specific cards to make sets of four.
• If the player has the card, they must hand it over; if not, they say “Go Fish,” and the asking player draws from the pond.
• The game ends when all sets are made, and the player with the most sets wins.

Buy here: Amazon

Best for Which Age: 6 years and up

Connect Four is all about strategic planning. Players aim to line up four discs in a row. This game challenges kids to think ahead and block their opponents, making it one of the most fun choice games for kids.

• Players choose a color and take turns dropping their colored discs into a vertically standing grid.
• The objective is to be the first to form a horizontal, vertical, or diagonal line of four of one’s discs.
• Players must strategize to block their opponent’s moves while working towards their four-in-a-row.
• The game ends when one player achieves a Connect Four or the grid fills up, indicating a tie.

Price: $12.51

Buy Here: Amazon

Mancala is a classic game that requires players to strategically move pieces around the board to capture more stones than their opponent. It’s a brilliant choice among decision making games for kids, teaching them to plan ahead and predict their opponent’s moves.

• The board is set up with an equal number of pieces in small pits.
• Players take turns picking up all the pieces in one of their pits and distributing them one by one in subsequent pits.
• The goal is to capture more pieces than the opponent by strategic placement and captures.

Price:  $12

Ticket to Ride: First Journey simplifies the classic game for younger audiences, focusing on strategic thinking as players plan train routes across a map. This making choices game is perfect for introducing basic strategy and planning skills to kids.

• Players collect train cards that enable them to claim railway routes on a map.
• The aim is to connect distant cities through a network of trains.
• Strategic planning is required to block opponents and efficiently connect cities.

Price:  $27

Catan Junior takes the beloved strategy game and simplifies it for younger players, focusing on resource management and basic strategic planning. It’s an excellent choice among decision making activities for elementary students, teaching them the importance of resource allocation and strategy.

• Players collect resources like wood and gold to build their pirate lairs.
• Trading resources with other players is a key part of the game.
• The first player to build all their pirate lairs wins, requiring careful planning and resource management.

Price:  $24.99

Best for Which Age: 7 years and up

Uno is a popular card game that combines strategy with luck, requiring players to adapt their strategies based on the cards they have and the actions of their opponents. It’s one of the most fun and engaging decision making activities for children, teaching them adaptability and strategic thinking.

• Players aim to match a card in their hand with the current card shown on top of the deck either by color or number.
• Special action cards, like skips and reverses, add complexity.
• The first player to rid themselves of all their cards wins, requiring strategic decision-making and adaptability to changing game dynamics.

Price:  $11.16

Chess is one of the best decision making games, teaching players to think several moves ahead and consider the consequences of their actions. It’s a classic game of strategy and tactics where every move counts.

• Each player starts with 16 pieces that move in specific ways across the board.
• The objective is to checkmate the opponent’s king, meaning the king is in a position to be captured and cannot escape.
• Players must protect their own pieces while strategizing to capture their opponent’s king.

Price:  $14.99

Battleship is a game that combines strategic planning and deduction, making it a great choice among decision making board games. Players guess the locations of their opponent’s ships and aim to sink them, all based on logical deduction and strategic thinking.

• Each player places their ships secretly on a grid.
• Players take turns calling out grid coordinates to guess the location of the opponent’s ships.
• The first player to sink all of the opponent’s ships wins.

Best for Which Age: 5 years and up

Guess Who? is a fun decision making situations game that enhances logical thinking and decision-making. Players ask yes or no questions to deduce the identity of the opponent’s character, using logic and deduction at every turn.

• Each player chooses a character card and places it in front of them.
• Players take turns asking yes or no questions to narrow down the possible characters their opponent has chosen.
• The first player to correctly guess the opponent’s character wins.

11. Clue (Cluedo)

Best for Which Age: 8 years and up

Clue, or Cluedo, is a classic among group decision making games, where players solve a mystery by deducing who committed the crime, with what weapon, and in which room. It’s a fantastic game for developing deductive reasoning and decision-making skills.

• Players move around the game board, which represents the rooms of a mansion, to collect clues.
• Through a process of elimination and deduction based on the clues gathered, players try to solve the mystery.
• The first player to correctly accuse the murderer, the weapon, and the room wins the game.

Price:  $17.99

12. Tic-Tac-Toe (Noughts and Crosses)

Tic-Tac-Toe, also known as Noughts and Crosses, is a perfect introductory decision making game for kids. It teaches young children the basics of strategy and foresight by encouraging them to think about their moves and anticipate their opponent’s next step.

• Players take turns marking a space in a 3×3 grid with their symbol, either a nought or a cross.
• The aim is to be the first to get three of your symbols in a row, either horizontally, vertically, or diagonally.
• Players need to block their opponent’s moves while working towards their own line of three.

13. Checkers (Draughts)

Checkers, known as Draughts in some countries, simplifies strategy and decision-making, making it one of the easiest decision making games for kids. It teaches them to plan their moves and predict their opponent’s actions in a straightforward, engaging way.

• Players move their pieces diagonally across a checkerboard, with the aim of capturing the opponent’s pieces by jumping over them.
• The game encourages players to protect their own pieces while finding opportunities to capture their opponent’s.
• The player who captures all of the opponent’s pieces wins.

Price:  $15.99

14. Rat-a-Tat Cat

Rat-a-Tat Cat is a card game that boosts memory and strategy through the use of card swaps and peeks. It’s a fun and engaging way to enhance decision-making skills in kids, as they must remember the cards’ values and decide the best times to swap.

• Players are dealt cards that they can peek at but then must keep face down, trying to remember the values.
• The aim is to end up with the lowest score by swapping out high-value cards for lower ones.
• Strategic thinking is required to decide when to swap cards and when to stick with what you have.

Price:  $11.99

15. Memory Game

The Memory Game, also known as Concentration, is a fantastic choice for kids to boost their memory and focus. By matching pairs of cards, children practice attention to detail and improve their recall abilities, making it a great pick from games on decision making.

• Spread all cards face down on a table.
• Players take turns flipping over two cards at a time.
• If the cards match, they keep them and go again.
• If they don’t match, they turn them back over, and the next player goes.
• The game continues until all pairs are matched.

Price:  $9.99

Decision making games for kids offer fun and interactive ways to boost critical thinking and problem-solving skills. These games not only keep children engaged but also play a crucial role in their cognitive development. So, let’s encourage our kids to play more of these games and watch them grow smarter every day!

Frequently Asked Questions (FAQs)

How do you teach children decision-making.

Teaching children decision-making involves guiding them through the process of making choices, discussing possible outcomes, and allowing them to experience the consequences in a safe environment. Encouraging them to weigh options and think ahead helps build this skill.

What is a decision-making game?

Decision making games for kids are an interactive activities designed to simulate scenarios where players must make choices, often within a set of rules or constraints, to achieve a goal or solve a problem, thereby sharpening their decision-making skills.

What is decision-making icebreaker activity?

A decision-making icebreaker activity is a short, engaging task that encourages participants to make choices and share their reasoning. It’s often used to warm up a group, foster teamwork, and introduce the concept of decision-making in a fun way.

What are some fun decision-making questions?

Fun decision-making questions can range from hypothetical scenarios like “Would you rather have the ability to fly or be invisible?” to practical choices such as “If you could only eat one food for the rest of your life, what would it be?” These fun would you rather questions stimulate thinking and conversation.

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