motivation study thesis

ORIGINAL RESEARCH article

The importance of students’ motivation for their academic achievement – replicating and extending previous findings.

• 1 Department of Psychology, TU Dortmund University, Dortmund, Germany
• 2 Department of Psychology, Philipps-Universität Marburg, Marburg, Germany
• 3 Department of Psychology, Heidelberg University, Heidelberg, Germany

Achievement motivation is not a single construct but rather subsumes a variety of different constructs like ability self-concepts, task values, goals, and achievement motives. The few existing studies that investigated diverse motivational constructs as predictors of school students’ academic achievement above and beyond students’ cognitive abilities and prior achievement showed that most motivational constructs predicted academic achievement beyond intelligence and that students’ ability self-concepts and task values are more powerful in predicting their achievement than goals and achievement motives. The aim of the present study was to investigate whether the reported previous findings can be replicated when ability self-concepts, task values, goals, and achievement motives are all assessed at the same level of specificity as the achievement criteria (e.g., hope for success in math and math grades). The sample comprised 345 11th and 12th grade students ( M = 17.48 years old, SD = 1.06) from the highest academic track (Gymnasium) in Germany. Students self-reported their ability self-concepts, task values, goal orientations, and achievement motives in math, German, and school in general. Additionally, we assessed their intelligence and their current and prior Grade point average and grades in math and German. Relative weight analyses revealed that domain-specific ability self-concept, motives, task values and learning goals but not performance goals explained a significant amount of variance in grades above all other predictors of which ability self-concept was the strongest predictor. Results are discussed with respect to their implications for investigating motivational constructs with different theoretical foundation.

Introduction

Achievement motivation energizes and directs behavior toward achievement and therefore is known to be an important determinant of academic success (e.g., Robbins et al., 2004 ; Hattie, 2009 ; Plante et al., 2013 ; Wigfield et al., 2016 ). Achievement motivation is not a single construct but rather subsumes a variety of different constructs like motivational beliefs, task values, goals, and achievement motives (see Murphy and Alexander, 2000 ; Wigfield and Cambria, 2010 ; Wigfield et al., 2016 ). Nevertheless, there is still a limited number of studies, that investigated (1) diverse motivational constructs in relation to students’ academic achievement in one sample and (2) additionally considered students’ cognitive abilities and their prior achievement ( Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ). Because students’ cognitive abilities and their prior achievement are among the best single predictors of academic success (e.g., Kuncel et al., 2004 ; Hailikari et al., 2007 ), it is necessary to include them in the analyses when evaluating the importance of motivational factors for students’ achievement. Steinmayr and Spinath (2009) did so and revealed that students’ domain-specific ability self-concepts followed by domain-specific task values were the best predictors of students’ math and German grades compared to students’ goals and achievement motives. However, a flaw of their study is that they did not assess all motivational constructs at the same level of specificity as the achievement criteria. For example, achievement motives were measured on a domain-general level (e.g., “Difficult problems appeal to me”), whereas students’ achievement as well as motivational beliefs and task values were assessed domain-specifically (e.g., math grades, math self-concept, math task values). The importance of students’ achievement motives for math and German grades might have been underestimated because the specificity levels of predictor and criterion variables did not match (e.g., Ajzen and Fishbein, 1977 ; Baranik et al., 2010 ). The aim of the present study was to investigate whether the seminal findings by Steinmayr and Spinath (2009) will hold when motivational beliefs, task values, goals, and achievement motives are all assessed at the same level of specificity as the achievement criteria. This is an important question with respect to motivation theory and future research in this field. Moreover, based on the findings it might be possible to better judge which kind of motivation should especially be fostered in school to improve achievement. This is important information for interventions aiming at enhancing students’ motivation in school.

Theoretical Relations Between Achievement Motivation and Academic Achievement

We take a social-cognitive approach to motivation (see also Pintrich et al., 1993 ; Elliot and Church, 1997 ; Wigfield and Cambria, 2010 ). This approach emphasizes the important role of students’ beliefs and their interpretations of actual events, as well as the role of the achievement context for motivational dynamics (see Weiner, 1992 ; Pintrich et al., 1993 ; Wigfield and Cambria, 2010 ). Social cognitive models of achievement motivation (e.g., expectancy-value theory by Eccles and Wigfield, 2002 ; hierarchical model of achievement motivation by Elliot and Church, 1997 ) comprise a variety of motivation constructs that can be organized in two broad categories (see Pintrich et al., 1993 , p. 176): students’ “beliefs about their capability to perform a task,” also called expectancy components (e.g., ability self-concepts, self-efficacy), and their “motivational beliefs about their reasons for choosing to do a task,” also called value components (e.g., task values, goals). The literature on motivation constructs from these categories is extensive (see Wigfield and Cambria, 2010 ). In this article, we focus on selected constructs, namely students’ ability self-concepts (from the category “expectancy components of motivation”), and their task values and goal orientations (from the category “value components of motivation”).

According to the social cognitive perspective, students’ motivation is relatively situation or context specific (see Pintrich et al., 1993 ). To gain a comprehensive picture of the relation between students’ motivation and their academic achievement, we additionally take into account a traditional personality model of motivation, the theory of the achievement motive ( McClelland et al., 1953 ), according to which students’ motivation is conceptualized as a relatively stable trait. Thus, we consider the achievement motives hope for success and fear of failure besides students’ ability self-concepts, their task values, and goal orientations in this article. In the following, we describe the motivation constructs in more detail.

Students’ ability self-concepts are defined as cognitive representations of their ability level ( Marsh, 1990 ; Wigfield et al., 2016 ). Ability self-concepts have been shown to be domain-specific from the early school years on (e.g., Wigfield et al., 1997 ). Consequently, they are frequently assessed with regard to a certain domain (e.g., with regard to school in general vs. with regard to math).

In the present article, task values are defined in the sense of the expectancy-value model by Eccles et al. (1983) and Eccles and Wigfield (2002) . According to the expectancy-value model there are three task values that should be positively associated with achievement, namely intrinsic values, utility value, and personal importance ( Eccles and Wigfield, 1995 ). Because task values are domain-specific from the early school years on (e.g., Eccles et al., 1993 ; Eccles and Wigfield, 1995 ), they are also assessed with reference to specific subjects (e.g., “How much do you like math?”) or on a more general level with regard to school in general (e.g., “How much do you like going to school?”).

Students’ goal orientations are broader cognitive orientations that students have toward their learning and they reflect the reasons for doing a task (see Dweck and Leggett, 1988 ). Therefore, they fall in the broad category of “value components of motivation.” Initially, researchers distinguished between learning and performance goals when describing goal orientations ( Nicholls, 1984 ; Dweck and Leggett, 1988 ). Learning goals (“task involvement” or “mastery goals”) describe people’s willingness to improve their skills, learn new things, and develop their competence, whereas performance goals (“ego involvement”) focus on demonstrating one’s higher competence and hiding one’s incompetence relative to others (e.g., Elliot and McGregor, 2001 ). Performance goals were later further subdivided into performance-approach (striving to demonstrate competence) and performance-avoidance goals (striving to avoid looking incompetent, e.g., Elliot and Church, 1997 ; Middleton and Midgley, 1997 ). Some researchers have included work avoidance as another component of achievement goals (e.g., Nicholls, 1984 ; Harackiewicz et al., 1997 ). Work avoidance refers to the goal of investing as little effort as possible ( Kumar and Jagacinski, 2011 ). Goal orientations can be assessed in reference to specific subjects (e.g., math) or on a more general level (e.g., in reference to school in general).

McClelland et al. (1953) distinguish the achievement motives hope for success (i.e., positive emotions and the belief that one can succeed) and fear of failure (i.e., negative emotions and the fear that the achievement situation is out of one’s depth). According to McClelland’s definition, need for achievement is measured by describing affective experiences or associations such as fear or joy in achievement situations. Achievement motives are conceptualized as being relatively stable over time. Consequently, need for achievement is theorized to be domain-general and, thus, usually assessed without referring to a certain domain or situation (e.g., Steinmayr and Spinath, 2009 ). However, Sparfeldt and Rost (2011) demonstrated that operationalizing achievement motives subject-specifically is psychometrically useful and results in better criterion validities compared with a domain-general operationalization.

Empirical Evidence on the Relative Importance of Achievement Motivation Constructs for Academic Achievement

A myriad of single studies (e.g., Linnenbrink-Garcia et al., 2018 ; Muenks et al., 2018 ; Steinmayr et al., 2018 ) and several meta-analyses (e.g., Robbins et al., 2004 ; Möller et al., 2009 ; Hulleman et al., 2010 ; Huang, 2011 ) support the hypothesis of social cognitive motivation models that students’ motivational beliefs are significantly related to their academic achievement. However, to judge the relative importance of motivation constructs for academic achievement, studies need (1) to investigate diverse motivational constructs in one sample and (2) to consider students’ cognitive abilities and their prior achievement, too, because the latter are among the best single predictors of academic success (e.g., Kuncel et al., 2004 ; Hailikari et al., 2007 ). For effective educational policy and school reform, it is crucial to obtain robust empirical evidence for whether various motivational constructs can explain variance in school performance over and above intelligence and prior achievement. Without including the latter constructs, we might overestimate the importance of motivation for achievement. Providing evidence that students’ achievement motivation is incrementally valid in predicting their academic achievement beyond their intelligence or prior achievement would emphasize the necessity of designing appropriate interventions for improving students’ school-related motivation.

There are several studies that included expectancy and value components of motivation as predictors of students’ academic achievement (grades or test scores) and additionally considered students’ prior achievement ( Marsh et al., 2005 ; Steinmayr et al., 2018 , Study 1) or their intelligence ( Spinath et al., 2006 ; Lotz et al., 2018 ; Schneider et al., 2018 ; Steinmayr et al., 2018 , Study 2, Weber et al., 2013 ). However, only few studies considered intelligence and prior achievement together with more than two motivational constructs as predictors of school students’ achievement ( Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ). Kriegbaum et al. (2015) examined two expectancy components (i.e., ability self-concept and self-efficacy) and eight value components (i.e., interest, enjoyment, usefulness, learning goals, performance-approach, performance-avoidance goals, and work avoidance) in the domain of math. Steinmayr and Spinath (2009) investigated the role of an expectancy component (i.e., ability self-concept), five value components (i.e., task values, learning goals, performance-approach, performance-avoidance goals, and work avoidance), and students’ achievement motives (i.e., hope for success, fear of failure, and need for achievement) for students’ grades in math and German and their GPA. Both studies used relative weights analyses to compare the predictive power of all variables simultaneously while taking into account multicollinearity of the predictors ( Johnson and LeBreton, 2004 ; Tonidandel and LeBreton, 2011 ). Findings showed that – after controlling for differences in students‘ intelligence and their prior achievement – expectancy components (ability self-concept, self-efficacy) were the best motivational predictors of achievement followed by task values (i.e., intrinsic/enjoyment, attainment, and utility), need for achievement and learning goals ( Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ). However, Steinmayr and Spinath (2009) who investigated the relations in three different domains did not assess all motivational constructs on the same level of specificity as the achievement criteria. More precisely, students’ achievement as well as motivational beliefs and task values were assessed domain-specifically (e.g., math grades, math self-concept, math task values), whereas students’ goals were only measured for school in general (e.g., “In school it is important for me to learn as much as possible”) and students’ achievement motives were only measured on a domain-general level (e.g., “Difficult problems appeal to me”). Thus, the importance of goals and achievement motives for math and German grades might have been underestimated because the specificity levels of predictor and criterion variables did not match (e.g., Ajzen and Fishbein, 1977 ; Baranik et al., 2010 ). Assessing students’ goals and their achievement motives with reference to a specific subject might result in higher associations with domain-specific achievement criteria (see Sparfeldt and Rost, 2011 ).

Taken together, although previous work underlines the important roles of expectancy and value components of motivation for school students’ academic achievement, hitherto, we know little about the relative importance of expectancy components, task values, goals, and achievement motives in different domains when all of them are assessed at the same level of specificity as the achievement criteria (e.g., achievement motives in math → math grades; ability self-concept for school → GPA).

The Present Research

The goal of the present study was to examine the relative importance of several of the most important achievement motivation constructs in predicting school students’ achievement. We substantially extend previous work in this field by considering (1) diverse motivational constructs, (2) students’ intelligence and their prior achievement as achievement predictors in one sample, and (3) by assessing all predictors on the same level of specificity as the achievement criteria. Moreover, we investigated the relations in three different domains: school in general, math, and German. Because there is no study that assessed students’ goal orientations and achievement motives besides their ability self-concept and task values on the same level of specificity as the achievement criteria, we could not derive any specific hypotheses on the relative importance of these constructs, but instead investigated the following research question (RQ):

RQ. What is the relative importance of students’ domain-specific ability self-concepts, task values, goal orientations, and achievement motives for their grades in the respective domain when including all of them, students’ intelligence and prior achievement simultaneously in the analytic models?

Materials and Methods

Participants and procedure.

A sample of 345 students was recruited from two German schools attending the highest academic track (Gymnasium). Only 11th graders participated at one school, whereas 11th and 12th graders participated at the other. Students of the different grades and schools did not differ significantly on any of the assessed measures. Students represented the typical population of this type of school in Germany; that is, the majority was Caucasian and came from medium to high socioeconomic status homes. At the time of testing, students were on average 17.48 years old ( SD = 1.06). As is typical for this kind of school, the sample comprised more girls ( n = 200) than boys ( n = 145). We verify that the study is in accordance with established ethical guidelines. Approval by an ethics committee was not required as per the institution’s guidelines and applicable regulations in the federal state where the study was conducted. Participation was voluntarily and no deception took place. Before testing, we received written informed consent forms from the students and from the parents of the students who were under the age of 18 on the day of the testing. If students did not want to participate, they could spend the testing time in their teacher’s room with an extra assignment. All students agreed to participate. Testing took place during regular classes in schools in 2013. Tests were administered by trained research assistants and lasted about 2.5 h. Students filled in the achievement motivation questionnaires first, and the intelligence test was administered afterward. Before the intelligence test, there was a short break.

Ability Self-Concept

Students’ ability self-concepts were assessed with four items per domain ( Schöne et al., 2002 ). Students indicated on a 5-point scale ranging from 1 (totally disagree) to 5 (totally agree) how good they thought they were at different activities in school in general, math, and German (“I am good at school in general/math/German,” “It is easy to for me to learn in school in general/math/German,” “In school in general/math/German, I know a lot,” and “Most assignments in school/math/German are easy for me”). Internal consistency (Cronbach’s α) of the ability self-concept scale was high in school in general, in math, and in German (0.82 ≤ α ≤ 0.95; see Table 1 ).

Table 1. Means ( M ), Standard Deviations ( SD ), and Reliabilities (α) for all measures.

Task Values

Students’ task values were assessed with an established German scale (SESSW; Subjective scholastic value scale; Steinmayr and Spinath, 2010 ). The measure is an adaptation of items used by Eccles and Wigfield (1995) in different studies. It assesses intrinsic values, utility, and personal importance with three items each. Students indicated on a 5-point scale ranging from 1 (totally disagree) to 5 (totally agree) how much they valued school in general, math, and German (Intrinsic values: “I like school/math/German,” “I enjoy doing things in school/math/German,” and “I find school in general/math/German interesting”; Utility: “How useful is what you learn in school/math/German in general?,” “School/math/German will be useful in my future,” “The things I learn in school/math/German will be of use in my future life”; Personal importance: “Being good at school/math/German is important to me,” “To be good at school/math/German means a lot to me,” “Attainment in school/math/German is important to me”). Internal consistency of the values scale was high in all domains (0.90 ≤ α ≤ 0.93; see Table 1 ).

Goal Orientations

Students’ goal orientations were assessed with an established German self-report measure (SELLMO; Scales for measuring learning and achievement motivation; Spinath et al., 2002 ). In accordance with Sparfeldt et al. (2007) , we assessed goal orientations with regard to different domains: school in general, math, and German. In each domain, we used the SELLMO to assess students’ learning goals, performance-avoidance goals, and work avoidance with eight items each and their performance-approach goals with seven items. Students’ answered the items on a 5-point scale ranging from 1 (totally disagree) to 5 (totally agree). All items except for the work avoidance items are printed in Spinath and Steinmayr (2012) , p. 1148). A sample item to assess work avoidance is: “In school/math/German, it is important to me to do as little work as possible.” Internal consistency of the learning goals scale was high in all domains (0.83 ≤ α ≤ 0.88). The same was true for performance-approach goals (0.85 ≤ α ≤ 0.88), performance-avoidance goals (α = 0.89), and work avoidance (0.91 ≤ α ≤ 0.92; see Table 1 ).

Achievement Motives

Achievement motives were assessed with the Achievement Motives Scale (AMS; Gjesme and Nygard, 1970 ; Göttert and Kuhl, 1980 ). In the present study, we used a short form measuring “hope for success” and “fear of failure” with the seven items per subscale that showed the highest factor loadings. Both subscales were assessed in three domains: school in general, math, and German. Students’ answered all items on a 4-point scale ranging from 1 (does not apply at all) to 4 (fully applies). An example hope for success item is “In school/math/German, difficult problems appeal to me,” and an example fear of failure item is “In school/math/German, matters that are slightly difficult disconcert me.” Internal consistencies of hope for success and fear of failure scales were high in all domains (hope for success: 0.88 ≤ α ≤ 0.92; fear of failure: 0.90 ≤ α ≤ 0.91; see Table 1 ).

Intelligence

Intelligence was measured with the basic module of the Intelligence Structure Test 2000 R, a well-established German multifactor intelligence measure (I-S-T 2000 R; Amthauer et al., 2001 ). The basic module of the test offers assessments of domain-specific intelligence for verbal, numeric, and figural abilities as well as an overall intelligence score (a composite of the three facets). The overall intelligence score is thought to measure reasoning as a higher order factor of intelligence and can be interpreted as a measure of general intelligence, g . Its construct validity has been demonstrated in several studies ( Amthauer et al., 2001 ; Steinmayr and Amelang, 2006 ). In the present study, we used the scores that were closest to the domains we investigated: overall intelligence, numerical intelligence, and verbal intelligence (see also Steinmayr and Spinath, 2009 ). Raw values could range from 0 to 60 for verbal and numerical intelligence, and from 0 to 180 for overall intelligence. Internal consistencies of all intelligence scales were high (0.71 ≤ α ≤ 0.90; see Table 1 ).

Academic Achievement

For all students, the school delivered the report cards that the students received 3 months before testing (t0) and 4 months after testing (t2), at the end of the term in which testing took place. We assessed students’ grades in German and math as well as their overall grade point average (GPA) as criteria for school performance. GPA was computed as the mean of all available grades, not including grades in the nonacademic domains Sports and Music/Art as they did not correlate with the other grades. Grades ranged from 1 to 6, and were recoded so that higher numbers represented better performance.

Statistical Analyses

We conducted relative weight analyses to predict students’ academic achievement separately in math, German, and school in general. The relative weight analysis is a statistical procedure that enables to determine the relative importance of each predictor in a multiple regression analysis (“relative weight”) and to take adequately into account the multicollinearity of the different motivational constructs (for details, see Johnson and LeBreton, 2004 ; Tonidandel and LeBreton, 2011 ). Basically, it uses a variable transformation approach to create a new set of predictors that are orthogonal to one another (i.e., uncorrelated). Then, the criterion is regressed on these new orthogonal predictors, and the resulting standardized regression coefficients can be used because they no longer suffer from the deleterious effects of multicollinearity. These standardized regression weights are then transformed back into the metric of the original predictors. The rescaled relative weight of a predictor can easily be transformed into the percentage of variance that is uniquely explained by this predictor when dividing the relative weight of the specific predictor by the total variance explained by all predictors in the regression model ( R 2 ). We performed the relative weight analyses in three steps. In Model 1, we included the different achievement motivation variables assessed in the respective domain in the analyses. In Model 2, we entered intelligence into the analyses in addition to the achievement motivation variables. In Model 3, we included prior school performance indicated by grades measured before testing in addition to all of the motivation variables and intelligence. For all three steps, we tested for whether all relative weight factors differed significantly from each other (see Johnson, 2004 ) to determine which motivational construct was most important in predicting academic achievement (RQ).

Descriptive Statistics and Intercorrelations

Table 1 shows means, standard deviations, and reliabilities. Tables 2 –4 show the correlations between all scales in school in general, in math, and in German. Of particular relevance here, are the correlations between the motivational constructs and students’ school grades. In all three domains (i.e., school in general/math/German), out of all motivational predictor variables, students’ ability self-concepts showed the strongest associations with subsequent grades ( r = 0.53/0.61/0.46; see Tables 2 –4 ). Except for students’ performance-avoidance goals (−0.04 ≤ r ≤ 0.07, p > 0.05), the other motivational constructs were also significantly related to school grades. Most of the respective correlations were evenly dispersed around a moderate effect size of | r | = 0.30.

Table 2. Intercorrelations between all variables in school in general.

Table 3. Intercorrelations between all variables in math.

Table 4. Intercorrelations between all variables in German.

Relative Weight Analyses

Table 5 presents the results of the relative weight analyses. In Model 1 (only motivational variables) and Model 2 (motivation and intelligence), respectively, the overall explained variance was highest for math grades ( R 2 = 0.42 and R 2 = 0.42, respectively) followed by GPA ( R 2 = 0.30 and R 2 = 0.34, respectively) and grades in German ( R 2 = 0.26 and R 2 = 0.28, respectively). When prior school grades were additionally considered (Model 3) the largest amount of variance was explained in students’ GPA ( R 2 = 0.73), followed by grades in German ( R 2 = 0.59) and math ( R 2 = 0.57). In the following, we will describe the results of Model 3 for each domain in more detail.

Table 5. Relative weights and percentages of explained criterion variance (%) for all motivational constructs (Model 1) plus intelligence (Model 2) plus prior school achievement (Model 3).

Beginning with the prediction of students’ GPA: In Model 3, students’ prior GPA explained more variance in subsequent GPA than all other predictor variables (68%). Students’ ability self-concept explained significantly less variance than prior GPA but still more than all other predictors that we considered (14%). The relative weights of students’ intelligence (5%), task values (2%), hope for success (4%), and fear of failure (3%) did not differ significantly from each other but were still significantly different from zero ( p < 0.05). The relative weights of students’ goal orientations were not significant in Model 3.

Turning to math grades: The findings of the relative weight analyses for the prediction of math grades differed slightly from the prediction of GPA. In Model 3, the relative weights of numerical intelligence (2%) and performance-approach goals (2%) in math were no longer different from zero ( p > 0.05); in Model 2 they were. Prior math grades explained the largest share of the unique variance in subsequent math grades (45%), followed by math self-concept (19%). The relative weights of students’ math task values (9%), learning goals (5%), work avoidance (7%), and hope for success (6%) did not differ significantly from each other. Students’ fear of failure in math explained the smallest amount of unique variance in their math grades (4%) but the relative weight of students’ fear of failure did not differ significantly from that of students’ hope for success, work avoidance, and learning goals. The relative weights of students’ performance-avoidance goals were not significant in Model 3.

Turning to German grades: In Model 3, students’ prior grade in German was the strongest predictor (64%), followed by German self-concept (10%). Students’ fear of failure in German (6%), their verbal intelligence (4%), task values (4%), learning goals (4%), and hope for success (4%) explained less variance in German grades and did not differ significantly from each other but were significantly different from zero ( p < 0.05). The relative weights of students’ performance goals and work avoidance were not significant in Model 3.

In the present studies, we aimed to investigate the relative importance of several achievement motivation constructs in predicting students’ academic achievement. We sought to overcome the limitations of previous research in this field by (1) considering several theoretically and empirically distinct motivational constructs, (2) students’ intelligence, and their prior achievement, and (3) by assessing all predictors at the same level of specificity as the achievement criteria. We applied sophisticated statistical procedures to investigate the relations in three different domains, namely school in general, math, and German.

Relative Importance of Achievement Motivation Constructs for Academic Achievement

Out of the motivational predictor variables, students’ ability self-concepts explained the largest amount of variance in their academic achievement across all sets of analyses and across all investigated domains. Even when intelligence and prior grades were controlled for, students’ ability self-concepts accounted for at least 10% of the variance in the criterion. The relative superiority of ability self-perceptions is in line with the available literature on this topic (e.g., Steinmayr and Spinath, 2009 ; Kriegbaum et al., 2015 ; Steinmayr et al., 2018 ) and with numerous studies that have investigated the relations between students’ self-concept and their achievement (e.g., Möller et al., 2009 ; Huang, 2011 ). Ability self-concepts showed even higher relative weights than the corresponding intelligence scores. Whereas some previous studies have suggested that self-concepts and intelligence are at least equally important when predicting students’ grades (e.g., Steinmayr and Spinath, 2009 ; Weber et al., 2013 ; Schneider et al., 2018 ), our findings indicate that it might be even more important to believe in own school-related abilities than to possess outstanding cognitive capacities to achieve good grades (see also Lotz et al., 2018 ). Such a conclusion was supported by the fact that we examined the relative importance of all predictor variables across three domains and at the same levels of specificity, thus maximizing criterion-related validity (see Baranik et al., 2010 ). This procedure represents a particular strength of our study and sets it apart from previous studies in the field (e.g., Steinmayr and Spinath, 2009 ). Alternatively, our findings could be attributed to the sample we investigated at least to some degree. The students examined in the present study were selected for the academic track in Germany, and this makes them rather homogeneous in their cognitive abilities. It is therefore plausible to assume that the restricted variance in intelligence scores decreased the respective criterion validities.

When all variables were assessed at the same level of specificity, the achievement motives hope for success and fear of failure were the second and third best motivational predictors of academic achievement and more important than in the study by Steinmayr and Spinath (2009) . This result underlines the original conceptualization of achievement motives as broad personal tendencies that energize approach or avoidance behavior across different contexts and situations ( Elliot, 2006 ). However, the explanatory power of achievement motives was higher in the more specific domains of math and German, thereby also supporting the suggestion made by Sparfeldt and Rost (2011) to conceptualize achievement motives more domain-specifically. Conceptually, achievement motives and ability self-concepts are closely related. Individuals who believe in their ability to succeed often show greater hope for success than fear of failure and vice versa ( Brunstein and Heckhausen, 2008 ). It is thus not surprising that the two constructs showed similar stability in their relative effects on academic achievement across the three investigated domains. Concerning the specific mechanisms through which students’ achievement motives and ability self-concepts affect their achievement, it seems that they elicit positive or negative valences in students, and these valences in turn serve as simple but meaningful triggers of (un)successful school-related behavior. The large and consistent effects for students’ ability self-concept and their hope for success in our study support recommendations from positive psychology that individuals think positively about the future and regularly provide affirmation to themselves by reminding themselves of their positive attributes ( Seligman and Csikszentmihalyi, 2000 ). Future studies could investigate mediation processes. Theoretically, it would make sense that achievement motives defined as broad personal tendencies affect academic achievement via expectancy beliefs like ability self-concepts (e.g., expectancy-value theory by Eccles and Wigfield, 2002 ; see also, Atkinson, 1957 ).

Although task values and learning goals did not contribute much toward explaining the variance in GPA, these two constructs became even more important for explaining variance in math and German grades. As Elliot (2006) pointed out in his hierarchical model of approach-avoidance motivation, achievement motives serve as basic motivational principles that energize behavior. However, they do not guide the precise direction of the energized behavior. Instead, goals and task values are commonly recruited to strategically guide this basic motivation toward concrete aims that address the underlying desire or concern. Our results are consistent with Elliot’s (2006) suggestions. Whereas basic achievement motives are equally important at abstract and specific achievement levels, task values and learning goals release their full explanatory power with increasing context-specificity as they affect students’ concrete actions in a given school subject. At this level of abstraction, task values and learning goals compete with more extrinsic forms of motivation, such as performance goals. Contrary to several studies in achievement-goal research, we did not demonstrate the importance of either performance-approach or performance-avoidance goals for academic achievement.

Whereas students’ ability self-concept showed a high relative importance above and beyond intelligence, with few exceptions, each of the remaining motivation constructs explained less than 5% of the variance in students’ academic achievement in the full model including intelligence measures. One might argue that the high relative importance of students’ ability self-concept is not surprising because students’ ability self-concepts more strongly depend on prior grades than the other motivation constructs. Prior grades represent performance feedback and enable achievement comparisons that are seen as the main determinants of students’ ability self-concepts (see Skaalvik and Skaalvik, 2002 ). However, we included students’ prior grades in the analyses and students’ ability self-concepts still were the most powerful predictors of academic achievement out of the achievement motivation constructs that were considered. It is thus reasonable to conclude that the high relative importance of students’ subjective beliefs about their abilities is not only due to the overlap of this believes with prior achievement.

Limitations and Suggestions for Further Research

Our study confirms and extends the extant work on the power of students’ ability self-concept net of other important motivation variables even when important methodological aspects are considered. Strength of the study is the simultaneous investigation of different achievement motivation constructs in different academic domains. Nevertheless, we restricted the range of motivation constructs to ability self-concepts, task values, goal orientations, and achievement motives. It might be interesting to replicate the findings with other motivation constructs such as academic self-efficacy ( Pajares, 2003 ), individual interest ( Renninger and Hidi, 2011 ), or autonomous versus controlled forms of motivation ( Ryan and Deci, 2000 ). However, these constructs are conceptually and/or empirically very closely related to the motivation constructs we considered (e.g., Eccles and Wigfield, 1995 ; Marsh et al., 2018 ). Thus, it might well be the case that we would find very similar results for self-efficacy instead of ability self-concept as one example.

A second limitation is that we only focused on linear relations between motivation and achievement using a variable-centered approach. Studies that considered different motivation constructs and used person-centered approaches revealed that motivation factors interact with each other and that there are different profiles of motivation that are differently related to students’ achievement (e.g., Conley, 2012 ; Schwinger et al., 2016 ). An important avenue for future studies on students’ motivation is to further investigate these interactions in different academic domains.

Another limitation that might suggest a potential avenue for future research is the fact that we used only grades as an indicator of academic achievement. Although, grades are of high practical relevance for the students, they do not necessarily indicate how much students have learned, how much they know and how creative they are in the respective domain (e.g., Walton and Spencer, 2009 ). Moreover, there is empirical evidence that the prediction of academic achievement differs according to the particular criterion that is chosen (e.g., Lotz et al., 2018 ). Using standardized test performance instead of grades might lead to different results.

Our study is also limited to 11th and 12th graders attending the highest academic track in Germany. More balanced samples are needed to generalize the findings. A recent study ( Ben-Eliyahu, 2019 ) that investigated the relations between different motivational constructs (i.e., goal orientations, expectancies, and task values) and self-regulated learning in university students revealed higher relations for gifted students than for typical students. This finding indicates that relations between different aspects of motivation might differ between academically selected samples and unselected samples.

Finally, despite the advantages of relative weight analyses, this procedure also has some shortcomings. Most important, it is based on manifest variables. Thus, differences in criterion validity might be due in part to differences in measurement error. However, we are not aware of a latent procedure that is comparable to relative weight analyses. It might be one goal for methodological research to overcome this shortcoming.

We conducted the present research to identify how different aspects of students’ motivation uniquely contribute to differences in students’ achievement. Our study demonstrated the relative importance of students’ ability self-concepts, their task values, learning goals, and achievement motives for students’ grades in different academic subjects above and beyond intelligence and prior achievement. Findings thus broaden our knowledge on the role of students’ motivation for academic achievement. Students’ ability self-concept turned out to be the most important motivational predictor of students’ grades above and beyond differences in their intelligence and prior grades, even when all predictors were assessed domain-specifically. Out of two students with similar intelligence scores, same prior achievement, and similar task values, goals and achievement motives in a domain, the student with a higher domain-specific ability self-concept will receive better school grades in the respective domain. Therefore, there is strong evidence that believing in own competencies is advantageous with respect to academic achievement. This finding shows once again that it is a promising approach to implement validated interventions aiming at enhancing students’ domain-specific ability-beliefs in school (see also Muenks et al., 2017 ; Steinmayr et al., 2018 ).

Data Availability

The datasets generated for this study are available on request to the corresponding author.

Ethics Statement

In Germany, institutional approval was not required by default at the time the study was conducted. That is, why we cannot provide a formal approval by the institutional ethics committee. We verify that the study is in accordance with established ethical guidelines. Participation was voluntarily and no deception took place. Before testing, we received informed consent forms from the parents of the students who were under the age of 18 on the day of the testing. If students did not want to participate, they could spend the testing time in their teacher’s room with an extra assignment. All students agreed to participate. We included this information also in the manuscript.

Author Contributions

RS conceived and supervised the study, curated the data, performed the formal analysis, investigated the results, developed the methodology, administered the project, and wrote, reviewed, and edited the manuscript. AW wrote, reviewed, and edited the manuscript. MS performed the formal analysis, and wrote, reviewed, and edited the manuscript. BS conceived the study, and wrote, reviewed, and edited the manuscript.

We acknowledge financial support by Deutsche Forschungsgemeinschaft and Technische Universität Dortmund/TU Dortmund University within the funding programme Open Access Publishing.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Keywords : academic achievement, ability self-concept, task values, goals, achievement motives, intelligence, relative weight analysis

Citation: Steinmayr R, Weidinger AF, Schwinger M and Spinath B (2019) The Importance of Students’ Motivation for Their Academic Achievement – Replicating and Extending Previous Findings. Front. Psychol. 10:1730. doi: 10.3389/fpsyg.2019.01730

Received: 05 April 2019; Accepted: 11 July 2019; Published: 31 July 2019.

Reviewed by:

Copyright © 2019 Steinmayr, Weidinger, Schwinger and Spinath. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

*Correspondence: Ricarda Steinmayr, [email protected]

Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

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8 Most Effective Ways to Increase Motivation for Thesis Writing 

Writing a master’s or doctoral thesis is a tough job, and many students struggle with writer’s block and putting off work. The journey requires not just skill and knowledge but a sustained motivation for thesis writing. Here are eight essential strategies to help you find and maintain your motivation to write your thesis throughout the thesis writing process.

Know why you lack motivation

It’s important to understand whether you’re just avoiding writing (procrastination) or if you genuinely don’t feel interested in it (lack of motivation). Procrastination is when you delay writing even though you want to finish it, while a lack of motivation for thesis writing is when you have no interest in writing at all. Knowing the difference helps you find the right solution. Remember, not feeling motivated doesn’t mean you can’t write; it just might be less enjoyable.

Recognize external vs. internal motivation

In the early stages of your academic journey, things like job prospects or recognition may motivate you to write your thesis. These are external motivators. Over time, they might become less effective. That’s why it’s important to develop internal motivators, like a real passion for your topic, curiosity, or wanting to make a difference in your field. Shifting to these internal motivators can keep you energized about your thesis writing for a longer period.

Develop a writing plan

As you regularly spend time on your thesis, you’ll start to overcome any initial resistance. Planning and thinking about your work will make the next steps easier. You might find yourself working more than 20 minutes some days. As you progress, plan for longer thesis writing periods and set goals for completing each chapter.

Don’t overwhelm yourself

Getting stuck is normal in thesis or dissertation writing. Don’t view these challenges as impossible obstacles. If you’re frustrated or unsure, take a break for a few days. Then, consult your advisor or a mentor to discuss your challenges and find ways to move forward effectively.

Work on your thesis daily

Try to spend 15-20 minutes daily on tasks related to your thesis or dissertation. This includes reading, researching, outlining, and other preparatory activities. You can fit these tasks into short breaks throughout your day, like waiting for appointments, during commutes, or even while cooking.

Understand that thesis writing motivation changes

Realize that thesis writing motivation isn’t always the same; it changes over time. Your drive to write will vary with different stages of your research and life changes. Knowing that motivation can go up and down helps you adapt. When you feel less motivated, focus on small, doable parts of your work instead of big, intimidating goals.

Recharge your motivation regularly

Just like you need to rest and eat well to keep your body energized, your motivation for thesis writing needs to be refreshed too. Do things that boost your mental and creative energy. This could be talking with colleagues, attending workshops, or engaging in hobbies that relax you. Stay aware of your motivation levels and take action to rejuvenate them. This way, you can avoid burnout and keep a consistent pace in your thesis work.

Keep encouraging yourself

Repeating encouraging phrases like “I will finish my thesis by year’s end” or “I’ll complete a lot of work this week” can really help. Saying these affirmations regularly can focus your energy and keep you on track with your thesis writing motivation .

Remember, the amount you write can vary each day. Some days you might write a lot, and other days less. The key is to keep writing, even if it’s just rough ideas or jumbled thoughts. Don’t let the need for perfection stop you. Listening to podcasts where researchers talk about their writing experiences can also be inspiring and motivate you in your writing journey.

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How to Write an INTRODUCTION Chapter (of a Thesis)

So it seems like you’ve read my previous article on how to develop a fantastic marketing or management thesis idea , right?

That is great. But perhaps now you have a clear idea of what to do for your research project but you don’t know exactly how to start your bachelor or masters thesis?

No worries! We’ve got your back. Here are some (hopefully) useful tips to do a great job and impress your supervisor and reviewers!

First of all: There is NO specific correct way to structure the Introduction chapter. But I suggest you cover the following structure:

***********************************************************

• Introduction

1.1 Personal Motivation

1.2 Research Aims and Objectives

       1.2.1 Aim

1.2.2 Objectives

1.3 Structure of the Thesis

Let’s discuss each topic in detail so that you don’t miss anything and can look impressively smart!

Imagine that your grandma is going to read your thesis and it is entitled “Applying Machine to Machine Interaction to Improve Sustainability Practices in Music Festivals”.

Would she know what “Machine to Machine Interaction” is? (Maybe she does and even more than us two put together!). But let’s assume she has no clue!

Would she know which sustainability practices are applied in music festivals? (Well, maybe she went to Woodstock in 1969, had an affair with Jimmy Hendrix and helped them reduce water consumption!). But let’s assume she has no clue of what it is!

This is exactly the point of an introduction! The reader (whoever he/she may be!) has to be able to read your introduction and have an OVERALL idea and be FAMILIARIZED with the CONTEXT of your study.

And how do you achieve it? SIMPLE. Do the following:

• What is it? When did it start?
• Which are they? What are examples of practices applied to music festivals?
• What is the trend within the industry sector/product type/service type you are discussing? In the last decade, has it increased? Decreased? How large is the global/regional market size? What are sales volumes of key players?
• Use RELIABLE sources for your data: renowned institutions and organizations, research groups, scientific publications.
• Make sure to REFERENCE all your data.

Video Support: Introduction Chapter 

In case you are enjoying the article, do not forget to watch the video with further support on how to write the introduction chapter of your thesis.

Here is the section of the thesis where you describe your motivation for conducting a study on this topic.

In other words: Explain why you are writing about “Applying Machine to Machine Interaction to Improve Sustainability Practices in Music Festivals” and not about any other random topic such as: “If there is life on other planets, aliens would also be fans of The Beatles”.

To explain your motivation and why you chose this topic you should ideally be very personal and even write this section in the first person ( other academics might disagree with me on this, but it’s ok ).

And keep this section SHORT. Two GOOD paragraphs should be enough.

Here it is VERY SIMPLE. You have read the recommendations on LiveInnovation.org on “ How to Develop a Research Project (or Thesis) Idea ”, right? NO? (Oh man, it’s not easy being your supervisor. Honestly!). So go check the site for it!

If you have, (Good on you, I’m proud!), then simply describe your aim in a sub-section 1.2.1 and 1.2.2 your objectives.

The objectives in 1.2.2 can even be stated in bullet points.

And here it is absolutely easy!

Even if you have a headache, you team has lost, you ran out of Oreo Ice cream Sandwich in the fridge and  your 6 year old neighbor is learning to play the violin, you can still write this section.

It will only take you one or two paragraphs to describe in GENERAL terms what will be discussed in the following chapters.

ONE SUGGESTION: Leave this for last and only write it once you have finished the entire thesis.

So basically you should have done the following in this chapter:

• First you have familiarized your reader with the context of your study, regardless of who is reading (Your former hippie grandma or Michael Jordan).
• You have familiarized the reader with YOU, by explaining WHY you are writing about this topic.
• You have explained what the thesis will be about.
• Finally you have anticipated the reader with what he/she/it will face on the coming chapters until the end of the thesis.

So now you are DONE with Chapter one and can focus on the rest of the thesis!

(In case you want to thank me later: I truly enjoy beer, Port wine and Whiskey).

Download the Recommendations

Did you like this article? Would like to have these recommendations with you while studying?

GREAT! Simply download the file here with all details:  LiveInnovation.org - Introduction Chapter of a Thesis.pdf

In case you would like to have more research suggestions, check our research resources section .

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A literature review on motivation

• Theoretical articles
• Published: 14 November 2013
• Volume 1 , pages 471–487, ( 2013 )

Cite this article

• Chandra Sekhar 1 ,
• Manoj Patwardhan 2 &
• Rohit Kr. Singh 3  

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Research on motivation has attracted academic and corporate entities over the last two decades. In the present study, authors have reviewed the intense literature to extract all possible dimensions of motivation, having direct and indirect impact on motivation techniques. This has examined the multidimensionality of motivation from the existing literature and present a conceptual framework based on it, and it is experienced that various motivation techniques (discussed in this study) are having a positive impact on both employee satisfaction and the quality of performance in the organization; however, the model needs to be validated using quantitative measures. In order to study the various issues highlighted in this paper related to employee motivation, a large body of literature mainly from different journals have been incorporated. To make the study more current only those studies were included which were published in the last two decades. In past research papers few dimensions of motivation were used to explain the different models motivation theory which has direct influence on employee motivation. The novelty of this study lies in its theoretical framework where authors have made an attempt to come up with a construct having dimensions that directly or indirectly influences employee motivation.

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Introduction

The ingredients of motivation lie within all and the internalized drive toward the dominant thought of the moment (Rabby 2001 ). Motivation directly links to individual performance that gain to organization performance and as a catalyzer for all individual employees working for an organization to enhance their working performance or to complete task in much better way than they usually do. Organization runs because of people working for it, and each person contributes toward achieving the ultimate goal of an organization. Panagiotakopoulos ( 2013 ) concluded that factors affecting staff motivation at a period where the financial rewards are kept to the least leads to stimulate employee performance. So, management personnel’s responsibility to motivate their employees to work as per the expectation to enhance the organization’s performance. Similarly Dysvik and Kuvaas ( 2010 ) concluded that intrinsic motivation was the strongest predictor of turnover intention and relationship between mastery-approach goals and turnover intention was only positive for employees, low in intrinsic motivation. The only thing organization needs to do is to give employees with ample resources and platform to do. As per Kuo ( 2013 ) a successful organization must combine the strengths and motivations of internal employees and respond to external changes and demands promptly to show the organization’s value. In this paper, we have taken various techniques of motivation from existing literature, and managed to make flow of motivation from young-age employees to old-age employees. From organization perspective managers need to understand the flow of motivation, it helps them to create a culture where employees always get motivated to do better. Barney and Steven Elias ( 2010 ) found that with extrinsic motivation there exist a significant interaction between job stress, flex time, and country of residence. Leaders know that at the heart of every productive and successful business lies a thriving organizational culture and hardworking people collaborate passionately to produce great results (Gignac and Palmer 2011 ). In the body of literature, various frameworks are used by the researchers based on theory of motivation, with only few dimensions of motivation.

Literature review

In a complex and dynamic environment, leader of the organization used to create the environment in which employee feel trusted and are empowered to take decisions in the organization which leads to enhance motivation level of employee and ultimately organizational performance are enhanced. Smith and Rupp ( 2003 ) stated that performance is a role of individual motivation; organizational strategy, and structure and resistance to change, is an empirical role relating motivation in the organization. Likewise, Luthans and Stajkovic ( 1999 ) concluded that advancement of human resources through rewards, monetary incentives, and organizational behavior modification has generated a large volume of debate in the human resource and sales performance field. According to Orpen ( 1997 ) better the relationship between mentors and mentees in the formal mentoring program, the more mentees are motivated to work hard and committed to their organization. Likewise, Malina and Selto ( 2001 ) conducted a case study in one corporate setting by using balance score card (BSC) method and found out that organizational outcomes would be greater if employees are provided with positive motivation. The establishment of operations-based targets will help the provision of strategic feedback by allowing the evaluation of actual performance against the operations-based targets. Goal-directed behavior and strategic feedback are expected to enhance organizational performance (Chenhall 2005 ). Kunz and Pfaff ( 2002 ) stated no substantive reason to fear an undermining effect of extrinsic rewards on intrinsic motivation. Decoene and Bruggeman ( 2006 ) in their study developed and illustrated a model of the relationship between strategic alignment, motivation and organizational performance in a BSC context and find that effective strategic alignment empowers and motivates working executives. Leaders motivate people to follow a participative design of work in which they are responsible and get it together, which make them responsible for their performance. Aguinis et al. ( 2013 ) stated that monetary rewards can be a very powerful determinant of employee motivation and achievement which, in turn, can advance to important returns in terms of firm-level performance. Garg and Rastogi ( 2006 ) identified the key issues of job design research and practice to motivate employees’ performance and concluded that a dynamic managerial learning framework is required to enhance employees’ performance to meet global challenges. Vuori and Okkonen ( 2012 ) stated that motivation helps to share knowledge through an intra-organizational social media platform which can help the organization to reach its goals and objectives. Den and Verburg ( 2004 ) found the impact of high performing work systems, also called human resource practices, on perceptual measures of firm performance. Ashmos and Duchon ( 2000 ) recognizes that employees have both a mind and a spirit and seek to find meaning and purpose in their work, and an aspiration to be part of a community, hence making their jobs worthwhile and motivating them to do at a high level with a view to personal and social development.

Methodology

The primary objective to write this review is to highlight the flow of motivation and reveals what motivation technique works more efficiently in different stages of life. This study provides useful managerial implication for employee motivation in an organization. The dimensions are made fit into a model that can benefit organization to enhance their performance; however, the model needs to validate through case study or quantitative study. To study the various issues highlighted in this study related to employee motivation, this study reviews a large body of literature mainly in different journals. Once all the issues have been identified, each issue is used as a keyword to search the relevant literature. To make the study more current only those studies are included which are published in the last two decades, while priority is given to studies which are published in the last decade. Table  1 shows that the number of articles or reviews published on motivation in the last two decades (Table  2 ).

Dimensions of motivation

Training refers to ‘‘the systematic accretion of skills, command, concepts or mindset leads to improve performance’’ (Lazazzara and Bombelli 2011 ). Baldwin et al. ( 1991 ) indicates that individuals with higher pre-training motivation on the basis of their willingness to attend training have greater learning outcomes as compared to individuals heaving lower pre-training motivation. Commeiras et al. ( 2013 ) point out that traineeship is continuing to grow. In business, context training basically refers to action of teaching employees and providing proper knowledge and skills to make themselves job fit as well as organization fit. Training teaches employees how to work and enhance their skills, hence motivate them to achieve the common goal of organization as well as of employee. In the today’s competitive world, every organization wants to achieve competitive edge over their competitors and be impossible to achieve without employee involvement, which forces management to motivate their employees by different means.

Monetary incentives

As summarized by Park ( 2010 ), monetary incentive acts as a stimulus for greater action and inculcates zeal and enthusiasm toward work, it helps an employee in recognition of achievement. Likewise, Beretti et al. ( 2013 ) discussed that monetary incentives used to build a positive environment and maintain a job interest, which is consistent among the employee and offer a spur or zeal in the employees for better performance. For reason, monetary incentive motivate employees and enhance commitment in work performance, and psychologically satisfy a person and leads to job satisfaction, and shape the behavior or outlook of subordinate toward work in the organization.

Job transfer

The work of Azizi and Liang ( 2013 ) indicated that workforce flexibility can be achieved by cross-training and improved via job rotation. In the same way, Eguchi ( 2004 ) concluded that job transfer plays a significant role in preventing workers from performing influence activities for private help. As summarized by Asensio-Cuesta et al. ( 2012 ) job rotation provides benefits to both workers and management in an organization and prevents musculoskeletal disorders, cast out fatigue and increases job satisfaction and morale. As a result, job transfer gives the opportunity to learn multiple skills and outlooks to the workers. It avoids the dullness caused by monotonous jobs and simultaneously brings smoothness in technological job with the help of handling different circumstances at different levels and it leads to effective learning of many aspects in the organization.

Job satisfaction

In ( 2011 ), Parvin and Kabir studied the tested factors affecting job satisfaction for pharmaceutical companies and described job satisfaction as how content an individual is with his or her job, and viewed job satisfaction is not the same as motivation, although clearly linked. Similarly, Pantouvakis and Bouranta ( 201 3) indicated job satisfaction as a consequence of physical features and as an antecedent of interactive features. Wickramasinghe ( 2009 ) investigated that gender and tenure are significant in job satisfaction measurement. So here it can be said that job satisfaction is often determined by how well outcome meet or exceed expectations. For example, a good work environment and good work conditions can increase employee job satisfaction and the employees will try to give their best which can increase the employee work performance.

A study by García et al. ( 2012 ) identified that perceptions of promotion systems affect organizational justice and job satisfaction. Likewise, Koch and Nafziger ( 2012 ) specified that promotions are desirable for most employees, only because they work harder to compensate for their “incompetence.” As a result, promotion at regular interval of time has an optimistic approach behind and they are generally given to satisfy the psychological requirements of employees in the organization.

Achievement

The work of Hunter et al. ( 2012 ) defines that achievement is a unique and specialized form of organizational performance. As per Satyawadi and Ghosh ( 2012 ), employees are motivated to a greater extent by achievement and self-control. Now this can be understood: an employee who is achievement motivated seeks achievement, bringing realistic but challenging goals, and betterment in the job. There is a strong need for feedback from the higher officials in the organization as to achievement and progress, and a need for a sense of attainment.

Working conditions

In ( 2012 ), Jung and Kim stated that good work environment and good work conditions can increase employee job satisfaction and an employee organizational commitment. So the employees will try to give their best which can increase the employee work performance. Similarly, Cheng et al. ( 2013 ) concluded that there were evidences of moderating effects of age on the associations between psychosocial work conditions and health. Now the importance and the need of working condition is so describing or defining the physical environment by identifying those elements or dimensions of the physical environment. Employees having poor working conditions will only provoke negative performance, since their jobs are mentally and physically demanding, they need good working conditions.

Appreciation

A study by Mahazril et al. ( 2012 ) organizations had the duty to appreciate the employee from time to time and offer other form of benefits such as payment, which will help in employee motivation. Likewise, Kingira and Mescib ( 2010 ) define appreciation as the abstract of immaterial incentives; “employees giving immaterial incentives (appreciation, respect etc.) as much as materiel incentives with working department” shows employees do not agree with this behavioral statement. With this result, it can be stated that employees being employed in different parts can take their different opinions at different levels. Among the variable of responsibility and being appreciated, it is understood that “success of employers always be appreciated with education.” The more effective quality and practicality of education employees had, the more contribution they will have to businesses.

Job security

As per Yamamoto ( 2013 ) if an employee perceives they will be getting rewards for good work and their job is a secured one, the performance will automatically be better. Similarly, Zhang and Wu ( 2004 ) indicated that with Job security, an employee gets confident with the future career and they put their most efforts to achieve the objectives of the organization. So we can say job satisfaction is the most influential tool of motivation and put the employee very far off from mental tension and he gives his best to the organization, ultimately it leads to profit maximization.

Recognition

According to Candi et al. ( 2013 ), a growing recognition of the opportunities of innovation is through experience staging. Mahazril et al. ( 2012 ) concluded that rewards and recognition and communication may motivate them to work. Recognition enhances the level of productivity and performance at job whether it is a first time performance or a repeated action at the job in a progressive way and ultimately reinforces the behavior of employee.

Social opportunities

In ( 2013 ), Harvey indicated that an employee is accepted as part of the social group or team. Most staff has an acute need that their contribution is worthwhile, appreciated, and acknowledged. Organizations need to look beyond the traditional economic incentives of career opportunities and salaries to other social and lifestyle factors outside the workplace. Similarly, Kingira and Mescib ( 2010 ) concluded that, different opinions between the employees in terms of behavioral statements which can be “Social opportunities providing at the highest level with working period leads the employee to achieve their goals of the organization.” Therefore, a social opportunity for the employee is used to boost their motivation level and ultimately helps in achieving the goals and objectives of the organization.

Figure  1 explains how motivation works in different stages of life, and motivation dimension plays a vital role in enhancing individual performance in different stages of life of human being. In the developed and developing nations around the world people experiencing the phenomenon of population aging i.e., participation of worker in their late career stage is low in the labor market. Levinson’s ( 1986 ) life stage model pointed out that adult life is characterized by a consecution of stages, such as early, middle, and late career stage, divided into various sub-stages and concerned with career development (comparable to the career stage model of Super (1984)). Here we have considered early career stage between 20 and 40; middle career stages between 40 and 54, and late career stage 55 and above. In an effort to set a threshold to define the older worker category, as anyone over age 55 (Finkelstein et al. 1995 ; Koc-Menard 2009 ).

Flow of motivation

In the early and middle stage of life, money is important to goal setting because offering such incentives bring person being more willing to expand effort to meet a given goal level than not offering the incentives. Given the willingness to expand effort, a goal tells the individual during different career stages where to expand effort, how much effort to exert, and how long to exert the effort. For example, younger employees early in their careers may have a propensity for higher immediate compensation and benefits, such as fully paid family medical plans or maternity/paternity leaves; because employees in later career stages might prefer stock options or most company contributions to their retirement plans. Wiley ( 1997 ) concluded that good pay is an important motivator regardless of age.

Figure  2 explains how motivation dimensions influence individual and organization performance. In this competitive environment, organizations works harder to integrate its workforce and to keep the coordination among employees to enhance the working as well as employee productivity. The positive impact of motivation works toward enhancing individual responsiveness toward work. Individual enhanced responsiveness help organization working that directly links toward increase in profit and increase in organization responsiveness. Customer will be more satisfied if organization shows fast response toward his/her queries and if organization takes responsibility to fulfill his demand.

Theoretical construct of research dimensions

If we talk the motivation dimension that enhances organization performance, training used to enhance the skills, efficiency, and knowledge of employees for doing a particular job during their earlier career stage because it familiarizes them with the organizations goals, rules, and regulations and the working conditions in one hand since updates and amendments take place in technology, purchasing a new equipment, changes in technique of production, and computer impartment. The employees are trained for use of new equipments and work methods. Training molds the thinking of employees and leads to quality performance of employees. Supervisors believe that older workers are less motivated to learn, less flexible, and do not want to take part in training programs. So, companies do not invest in training or development opportunities for older people. In turn, older workers become less self-confident due to the lack of support in terms of training and their skills rapidly become outdated (Maurer 2001 ; Van Vianen et al. 2011 ).

Giving a job security to an employee makes him more responsible toward job. Job security can be explained as, affirmation that an employee has for the continuity of gainful employment for his or her job. It is more essential for younger employee during different career stages of life (job) because it arises from the terms of contract of employment, labor legislation that results in prevention of arbitrary termination, layoffs, and lockout. Likewise, Pravin and Kabir ( 2011 ) indicated that with job security in pharmaceutical companies employee is “neither happy nor unhappy” and hence influence job satisfaction in pharmaceutical companies. Job security has been considered from several theoretical perspectives, including as a motivational precursor to job performance.

Employee recognition is used to fulfill the inherent need to appreciate as well as work to be validated by the employee contribution. During the early and later stage of life of the employee, the most important tool to motivate the employee by recognizing positive behavior from employees means that those desired behaviors that drive business success will be reciprocated. Recognition is essential to an outstanding workplace because people want to be respected and valued for their contribution. Recognizing employee for their good work sends an extremely powerful message to the recipient, their work team, and other employees through formal and informal communication channels. Employee recognition is a dynamic communication technique to improve employee performance which leads to enhance organizational performance.

In an organization, it is important to make the employees valued and appreciated, because of which they get motivated and they work harder and be more loyal toward the organization. During the early and middle career stage of the job employee want more appreciation from his next boss in the organization. Many ways of appreciating employee are news for companies looking for inexpensive ways to show appreciation to employees who made an appreciative effort, to thank employees several times a week, often through notes mailed to their homes and admits an employee-of-the-month program, the least time-consuming way to make sure his staff continued to appreciate.

In an organization employees have the opportunity to transfer to another job if they are moving or have the want to switch occupations. It brings positive energy among the early career stage employee to work in a new environment, which gives workers the opportunity to learn multiple skills and outlooks. When employees continue working at the same tasks for an extended time, they are likely to build tight relationships with particular individuals and companies, which can yield help to the employees, and to the organization.

In the early stage of the employee, they used to seek the working environment and aspects of an employee’s terms and conditions of employment. This includes the employee payment, organization of work, and work activities; training, skills, and employability; amenities, physical environment, health, safety, and well-being; and working time and work–life balance. These used to motivate the employee to do better and achieve the organizational goals and objectives. Changes in working conditions and other aspects of the employment relationship can generate serious industrial relations problems.

Williams et al. ( 2003 ) argues that the job satisfaction works toward making good relationships with staff and colleagues, control of time off, enough resources, and bring autonomy for employee in the organization. It is essential in the stages of employment i.e., early, middle, and late career stage of life because it brings any combination of physiological, psychological, satisfaction that invokes a person truthfully to say I am satisfied with my current job and it leads to employee motivation to achieve goals of the organization. Job satisfaction refers doing a job one enjoys, and being rewarded for one’s accomplishment. It is the key ingredient that leads to recognition, income, promotion, and the achievement of other goals that lead to a feeling of fulfillment of the desired goals and objectives (Kaliski 2007 ).

In the middle and late career stages of their employment, employees have an opportunity to showcase their achievements with pride. Employees work in organizations not just to make a living, but to make a life. It encourages heightened ownership at work. Tangible benefits (salary) and intangible benefits (achievements of the knowledge) and other perks are necessary to engage employees, and motivate them to do their personal best. Mehta et al. ( 2000 ) pointed out that four most highly ranked rewards for sales managers in the late career stage have mean values that exceed 6.0, which includes achievement of market goals, retaining respect of salespeople, opportunities for promotion, and bonus.

A motivated and dedicated employee in the middle career stage of their job in the organization is an asset for any organization and proves instrumental in building a high-performance culture that drives organizational advancement. Promotion is always employee’s ultimate wish for the service rendered by him in the organization and this is the only way for an employee career development. Promotion is the ultimate motivating for any employee because it moves employee forward in hierarchy of concern organization added with other responsibility, higher respect, honors, with increase in grade pay and allowances. It stimulates self-development and creates interest in the job in one hand and minimizes discontent and unrest.

In the late career stage of their employment social opportunities for employees to get involved in leveraging the core competencies of the organization to create business value and positive social change can increase employee motivation and job satisfaction and help workers to more effectively manage job stress. This can lead to positive gains for the organization by enhancing organizational effectiveness and improving work quality, as well as by helping the organization attract and keep top-quality employees, which can bring growth and development to the organizations and can improve the quality of their employees’ work experience and realize the benefits of developing workers to their full potential.

Concluding remarks

Motivation works as a catalyzer for individual employees working for an organization to enhance their working performance or to complete task in much better way than they usually do. In this paper, authors identified the key motivation techniques from existing literature and linked it through organization performance. These motivation techniques has long been acknowledged as an important personnel work with the potential to improve employee motivation and hence performance, and to deliver management with the control needed to achieve organizational objectives. Authors made flow of motivation from early career motivation techniques to late career motivation techniques and reached on a conclusion: if employees are provided with right motivation technique at right time, their morale and confidence goes up and had a direct positive impact in individual performance and organizational performance. It is indicative of the above discussion, most of the motivation dimensions viz. training, monetary incentives, promotion, and working conditions has been met and for reason the efforts made to motivate are bound to succeed. This conclusion is built on the emphasis made by earlier researchers to motivate people, organizations need to first have the baseline in place; in the absence of the baseline, motivation is not possible to achieve. The study has shown success in intrinsic motivators and extrinsic motivators to improve performance in the organization.

The major limitation of this study is that the proposed framework is designed on basis of extensive literature review and so needs to be confirmed using quantitative measures. This framework is not been implemented in specific industry, due to its generality in nature. Although extensive research is reviewed and every possible dimensions of motivation are studied, it cannot be stated explicitly that these dimensions will be able to create the baseline which will motivate the employees through the motivators. Thus, they create a dilemma as to whether these motivation dimensions are enough to create a solid baseline which has an impact on the motivators.

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Sekhar, C., Patwardhan, M. & Singh, R.K. A literature review on motivation. Glob Bus Perspect 1 , 471–487 (2013). https://doi.org/10.1007/s40196-013-0028-1

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DOI : https://doi.org/10.1007/s40196-013-0028-1

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Thesis Chapters 1-3 (2) motivation

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Use of serious games and gamified applications for language learning have increased substantially over the past decade. They are an effective way to supplement language learning. These applications utilize a range of language learning methods such as grammar-translation, audio-lingual and task-based learning in combination. Task-based language learning particularly suits the typical gameplay elements of narratives and quests. Thus, this study aims to develop a serious game for learning Bengali, world’s 7th most spoken language. The literature in this area indicates that hubshaped quest landscape design is found to be most effective for game-based learning environments. So, the study implements a branching, hubshaped narrative for learning Bengali language.

This application also implemented a hidden object mechanism for vocabulary acquisition instead of traditional grammar-translation methods used in other language learning software. The prototype was assessed from user feedback in a qualitative manner across four broad heuristic categories comprising of learning, tutorials, engagement and cultural elements. In the process, the study sought to understand whether cultural context-based interventions in the narrative improve learner motivation.

The results show a positive impact of cultural elements on the learners’ motivation to progress. Further, the hidden object mechanism was received as a satisfactory method to learn foreign vocabulary. This form of interactive, narrative based educational application has the potential to supplement traditional lessons for foreign language acquisition.

Degree Type

• Master of Science
• Computer Graphics Technology

Campus location

• West Lafayette

Advisor/Supervisor/Committee Chair

Additional committee member 2, additional committee member 3, usage metrics.

• Entertainment and gaming
• Interactive narrative
• Serious games
• Indian languages