Chinese undergraduate students' motivation profiles: Identification and significance

<p>This research sought to investigate the motivation of Chinese undergraduate students. It drew on Higgins’ (2012) conceptualization of motivation, which defined motivation as involving individuals’ simultaneous strivings for value, truth, and control effectiveness. Promotion, prevention, assessment, and locomotion are key general motivation tendencies that measure these three ways of strivings for effectiveness; these motivation tendencies interact to shape motivation effects (Higgins, 2012). This research examined the number and nature of the motivation configurations (i.e., motivation profiles) that mapped the interrelationships among promotion, prevention, assessment, and locomotion for a sample of Chinese undergraduate students. To this end, a mixed methods approach was adopted. First, quantitative data were collected from 886 Chinese undergraduate students at a Chinese university. The quantitative phase identified the motivation profiles and evaluated similarities/differences among the profiles with regard to important motivation factors pertaining to grit, theories of intelligence, critical thinking, effort regulation, and perceptions/evaluations of academic success. Then, the qualitative phase consisted of a multiple-case study of 19 interview participants who were purposefully selected from each of the motivation profiles identified in the quantitative phase. Analyses of quantitative and qualitative data revealed important findings. Specifically, five distinct motivation profiles were determined in the quantitative phase. The first profile (i.e., C1) was characterized by having high/very high and comparable levels of all four motivation orientations. The C2 profile encompassed very strong prevention and average and comparable levels of the remaining orientations. The C3 profile was characterized by strong/very strong and comparable assessment, locomotion, and promotion, but very weak prevention. The C4 profile was characterized by having low/very low levels of assessment, locomotion, and promotion and below average levels of prevention. The C5 profile encompassed below average and comparable levels of assessment, locomotion, promotion, and somewhat stronger prevention. Subsequent analyses showed that there were statistically significant differences among the profiles with regard to most of the motivation factors investigated. Some of these differences were of medium to large/very large magnitude. The qualitative phase of this research provided an in-depth understanding of the different strategic approaches that students who have a certain motivation profile reported employing in their learning. The qualitative findings showed that the approaches to learning and learning related tasks/activities that were reported by the interview participants were generally in line with the characteristics of their motivation profiles. Identifying and discussing Chinese undergraduate students’ motivation profiles contribute to understanding how the four general motivation tendencies (i.e., promotion, prevention, assessment, and locomotion) interact and how these interactions shape other motivation factors for this population. Moreover, findings from this research provide salient information regarding the motivation factors that undergird students’ academic success. This knowledge can help teachers/educators better understand students’ motivation and support productive outcomes in learning settings. In conclusion, this research makes important contributions to the existing motivation literature and educational practices. It also opens up novel directions for future research.</p>

Chinese undergraduate students' motivation profiles: Identification and significance

<p>This research sought to investigate the motivation of Chinese undergraduate students. It drew on Higgins’ (2012) conceptualization of motivation, which defined motivation as involving individuals’ simultaneous strivings for value, truth, and control effectiveness. Promotion, prevention, assessment, and locomotion are key general motivation tendencies that measure these three ways of strivings for effectiveness; these motivation tendencies interact to shape motivation effects (Higgins, 2012). This research examined the number and nature of the motivation configurations (i.e., motivation profiles) that mapped the interrelationships among promotion, prevention, assessment, and locomotion for a sample of Chinese undergraduate students. To this end, a mixed methods approach was adopted. First, quantitative data were collected from 886 Chinese undergraduate students at a Chinese university. The quantitative phase identified the motivation profiles and evaluated similarities/differences among the profiles with regard to important motivation factors pertaining to grit, theories of intelligence, critical thinking, effort regulation, and perceptions/evaluations of academic success. Then, the qualitative phase consisted of a multiple-case study of 19 interview participants who were purposefully selected from each of the motivation profiles identified in the quantitative phase. Analyses of quantitative and qualitative data revealed important findings. Specifically, five distinct motivation profiles were determined in the quantitative phase. The first profile (i.e., C1) was characterized by having high/very high and comparable levels of all four motivation orientations. The C2 profile encompassed very strong prevention and average and comparable levels of the remaining orientations. The C3 profile was characterized by strong/very strong and comparable assessment, locomotion, and promotion, but very weak prevention. The C4 profile was characterized by having low/very low levels of assessment, locomotion, and promotion and below average levels of prevention. The C5 profile encompassed below average and comparable levels of assessment, locomotion, promotion, and somewhat stronger prevention. Subsequent analyses showed that there were statistically significant differences among the profiles with regard to most of the motivation factors investigated. Some of these differences were of medium to large/very large magnitude. The qualitative phase of this research provided an in-depth understanding of the different strategic approaches that students who have a certain motivation profile reported employing in their learning. The qualitative findings showed that the approaches to learning and learning related tasks/activities that were reported by the interview participants were generally in line with the characteristics of their motivation profiles. Identifying and discussing Chinese undergraduate students’ motivation profiles contribute to understanding how the four general motivation tendencies (i.e., promotion, prevention, assessment, and locomotion) interact and how these interactions shape other motivation factors for this population. Moreover, findings from this research provide salient information regarding the motivation factors that undergird students’ academic success. This knowledge can help teachers/educators better understand students’ motivation and support productive outcomes in learning settings. In conclusion, this research makes important contributions to the existing motivation literature and educational practices. It also opens up novel directions for future research.</p>

Measuring Those Who Have Their Minds Set: An Item-Level Meta-Analysis of the Implicit Theories of Intelligence Scale in Education

Fixed and growth mindsets represent implicit theories about the nature of one’s abilities or traits. The existing body of research on academic achievement and the effectiveness of mindset interventions for student learning largely relies on the premise that fixed and growth mindsets are mutually exclusive. This premise has led to the common practice in which measures of one mindset are reversed and then assumed to represent the other mindset. Focusing on K-12 and university students (N = 27328), we tested the validity of this practice via a comprehensive item-level meta-analysis of the Implicit Theories of Intelligence Scale (ITIS). By means of meta-analytic structural equation modeling and network analysis, we examined (a) the ITIS item-item correlations and their heterogeneity across 32 primary studies; (b) the factor structure of the ITIS, including the distinction between fixed and growth mindset; and (c) moderator effects of sample, study, and measurement characteristics. We found positive item-item correlations within the sets of fixed and mindset items, with substantial between-study heterogeneity. The ITIS factor structure comprised two moderately correlated mindset factors (ρ = .63–.65), even after reversing one mindset scale. This structure was moderated by the educational level and origin of the student sample, the assessment mode, and scale modifications. Overall, we argue that fixed and growth mindsets are not mutually exclusive but correlated constructs. We discuss the implications for the assessment of implicit theories of intelligence in education.

Identified Motivation as a Key Factor for School Engagement During the COVID-19 Pandemic-Related School Closure

On March 16, 2020, French schools suddenly closed due to the COVID-19 pandemic, and middle school students were asked to study from home with no direct interactions with teachers or classmates. However, school plays an important role in the development of social, intellectual, and mental competencies and can counteract the negative effects of adverse life events on learning and early school dropout. In this study, we investigated how the unusual context of school closure during the COVID-19 pandemic affected school engagement. Specifically, we focused on inter-individual differences in the motivational determinants of school engagement. We thus performed an online survey of 170 students focusing on the time spent on mathematics assignments, motivation regulation, implicit theories of intelligence, such as adopting a growth or a fixed mindset about his/her intellectual abilities, and optimism. Importantly, the students participated in the online survey during the first lockdown period, with schools closed (T1), and the second lockdown period, with schools remaining open (T2). During T1, identified motivation positively predicted the time spent on math homework assignments: the more the students thought that working on math exercises was useful for their future life, the more time they spent studying. Importantly, the link between identified motivation and school engagement was specific to T1, when schools were closed, as indicated by a significant interaction between identified motivations by type of lockdown. These results suggest that having self-determined motivation is of particular importance when students are deprived of social and intellectual interactions with classmates and teachers. This finding paves the way toward the development of wise rational interventions that target identified motivation and can be applied during challenging societal times and adverse, common life events to keep students engaged with school.

The Mindset of Intelligence Is Not a Contributor of Placebo Effects in Working Memory Training

Whether working memory training is effective in enhancing fluid intelligence remains in dispute. Several researchers, who doubt the training benefits, consider that placebo effects may be the reason for positive training gains. One of the vital variables that may induce the placebo effect is the mindset of intelligence. In this article, we provide a test of whether the mindset of intelligence leads to placebo effects in working memory training. Participants were overtly recruited and allocated to the growth mindset group or the fixed mindset group by Theories of Intelligence Scale scores. A single, 1 h session working memory training is the cue to introduce the placebo effects. During pre/post-testing, all participants completed tasks measuring working memory capacity (near transfer) and fluid intelligence (far transfer). Our findings show no significant difference between the two groups in both tasks. Therefore, these results suggest that the placebo effect does not exist in this study, which means individuals' mindset of intelligence may not be a contributor to the placebo effect in 1 h working memory training. This research will further help to clarify the mechanism of the placebo effect in working memory training.

Dispositional Learning Analytics for Supporting Individualized Learning Feedback

An important goal of learning analytics (LA) is to improve learning by providing students with meaningful feedback. Feedback is often generated by prediction models of student success using data about students and their learning processes based on digital traces of learning activities. However, early in the learning process, when feedback is most fruitful, trace-data-based prediction models often have limited information about the initial ability of students, making it difficult to produce accurate prediction and personalized feedback to individual students. Furthermore, feedback generated from trace data without appropriate consideration of learners’ dispositions might hamper effective interventions. By providing an example of the role of learning dispositions in an LA application directed at predictive modeling in an introductory mathematics and statistics module, we make a plea for applying dispositional learning analytics (DLA) to make LA precise and actionable. DLA combines learning data with learners’ disposition data measured through for example self-report surveys. The advantage of DLA is twofold: first, to improve the accuracy of early predictions; and second, to link LA predictions with meaningful learning interventions that focus on addressing less developed learning dispositions. Dispositions in our DLA example include students’ mindsets, operationalized as entity and incremental theories of intelligence, and corresponding effort beliefs. These dispositions were inputs for a cluster analysis generating different learning profiles. These profiles were compared for other dispositions and module performance. The finding of profile differences suggests that the inclusion of disposition data and mindset data, in particular, adds predictive power to LA applications.

Multiple-Goal Approach Among Indonesian University Students

A total of 1006 students from three public and two private universities in Indonesia participated in the study of multiple goals profiling in the Indonesian context. Four multiple-goal clusters, with learning, performance approach, performance avoidance, and work avoidance goals as clustering variables, were educed. Learning goals correlated positively with both performance approach and performance avoidance clusters, and negatively to work avoidance goals. Performance goals correlated positively with both performance avoidance and work avoidance goals. Learning, performance approach and performance avoidance goals correlated positively with self-efficacy. These clusters were further examined in relations to attributions, self-efficacy, theories of intelligence, religiosity, racial/ethnic identity, and academic performance.

Intelligence Beliefs Predict Spatial Performance in Virtual Environments and Graphical Creativity Performance

Although intelligence beliefs have been applied to explain the influence of cognition, behavior, and creativity, the research on creativity is still limited. Therefore, in order to effectively expand the understanding of the influence of intelligence beliefs on the creative performance of learners’ graphics, the implicit theories of intelligence were exploited as the basis of this study. Three hypothetical pathways were proposed to be explored, and a research model was validated. First- and second-year students from a technical high school in New Taipei City were invited to participate. There were 273 valid data (88.9% of complete data). Reliability and validity analyses were performed, as well as overall model fit analysis and research model validation, and descriptive statistical analysis of the learners’ performance in applying the operational virtual reality (VR). The results of this study showed that: (1) Incremental beliefs of aesthetic intelligence had a positive effect on spatial performance; (2) entity belief of spatial intelligence (EBSI) had a negative effect on spatial performance; and (3) spatial performance had a positive effect on graphical design performance. From the results, it is clear that design teachers can assess students’ implicit beliefs in the early stages of teaching to actively promote better spatial performance when students show high levels of entity beliefs.

Reconsidering the Use of the Mindset Assessment Profile in Educational Contexts

The Mindset Assessment Profile is a popular questionnaire purportedly designed to measure mindset—an individual’s belief in whether intelligence is malleable or stable. Despite its widespread use, the questionnaire appears to assess an individual’s need for cognition and goal orientation more than mindset. We assessed the reliability, construct validity, and factor structure of the Mindset Assessment Profile in a sample of 992 undergraduates. The reliability of the Mindset Assessment Profile was questionable (α = .63) and significantly lower than the reliability of the Implicit Theories of Intelligence Questionnaire (α = .94), an established measure of mindset. The Mindset Assessment Profile also lacked convergent and discriminant validity. Overall scores on the Mindset Assessment Profile correlated significantly more strongly with need for cognition than with mindset. Item-level analyses supported this finding: most items correlated weakly or not at all with mindset, and correlated significantly more strongly with need for cognition and learning goal orientation. Exploratory factor analysis indicated that three factors were underlying scores on the Mindset Assessment Profile: need for cognition, mindset, and performance goal orientation. Based on its questionable reliability and poor construct validity, we do not recommend that researchers and educators use the Mindset Assessment Profile to measure mindset.