An official website of the United States government
Well-designed instructional videos are powerful tools for helping students learn and prompting students to use generative strategies while learning from videos further bolsters their effectiveness. However, little is known about how individual differences in motivational factors, such as achievement goals, relate to how students learn within multimedia environments that include instructional videos and generative strategies. Therefore, in this study, we explored how achievement goals predicted undergraduate students’ behaviors when learning with instructional videos that required students to answer practice questions between videos, as well as how those activities predicted subsequent unit exam performance one week later. Additionally, we tested the best measurement models for modeling achievement goals between traditional confirmatory factor analysis and bifactor confirmatory factor analysis. The bifactor model fit our data best and was used for all subsequent analyses. Results indicated that stronger mastery goal endorsement predicted performance on the practice questions in the multimedia learning environment, which in turn positively predicted unit exam performance. In addition, students’ time spent watching videos positively predicted practice question performance. Taken together, this research emphasizes the availing role of adaptive motivations, like mastery goals, in learning from instructional videos that prompt the use of generative learning strategies.
more »
« less
Investigating bifactor modeling of biology undergraduates’ task values and achievement goals across semesters.
Undergraduate science, technology, engineering, and mathematics (STEM) students’ motivations have a strong influence on whether and how they will persist through challenging coursework and into STEM careers. Proper conceptualization and measurement of motivation constructs, such as students’ expectancies and per- ceptions of value and cost (i.e., expectancy value theory [EVT]) and their goals (i.e., achievement goal theory [AGT]), are necessary to understand and enhance STEM persistence and success. Research findings suggest the importance of exploring multiple measurement models for motivation constructs, including traditional con- firmatory factor analysis, exploratory structural equation models (ESEM), and bifactor models, but more research is needed to determine whether the same model fits best across time and context. As such, we mea- sured undergraduate biology students’ EVT and AGT motivations and investigated which measurement model best fit the data, and whether measurement invariance held, across three semesters. Having determined the best- fitting measurement model and type of invariance, we used scores from the best performing model to predict biology achievement. Measurement results indicated a bifactor-ESEM model had the best data-model fit for EVT and an ESEM model had the best data-model fit for AGT, with evidence of measurement invariance across semesters. Motivation factors, in particular attainment value and subjective task value, predicted small yet statistically significant amounts of variance in biology course outcomes each semester. Our findings provide support for using modern measurement models to capture students’ STEM motivations and potentially refine conceptualizations of them. Such future research will enhance educators’ ability to benevolently monitor and support students’ motivation, and enhance STEM performance and career success.
more »
« less
- Award ID(s):
- 1821594
- PAR ID:
- 10487839
- Publisher / Repository:
- American Psychological Association
- Date Published:
- Journal Name:
- Journal of Educational Psychology
- Volume:
- 115
- Issue:
- 6
- ISSN:
- 0022-0663
- Page Range / eLocation ID:
- 836 to 858
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
null (Ed.)The current COVID-19 pandemic has forced many colleges and universities to remain on a completely online or remote educational learning environment for the 2020 Spring and Fall semesters, however there is a growing concern in STEM fields about how students will be able to achieve one of the major ABET learning outcomes without conducting physical, hands on laboratory exercises as many STEM disciplines are switching to virtual laboratory; an ability to develop and conduct appropriate experimentation, analyze and interpret data, and use engineering/scientific judgment to draw conclusions. In addition to the limited achievement of the ABET outcomes, roughly half of the population of a historically black university communicated their anxieties during the pandemic to the University President via Change.org. The students’ main anxiety is portrayed in a statement culled from the petition as follows: “Most classes are very hands-on, and we are not able to do those from home because of the limited resources available at home”. This paper highlights the best practices for the implementation of home-based hands-on activities across multiple STEM fields. The paper further elaborates on the impact of remote and virtual labs on students’ attitude, interest, and performance in STEM over the home-based hands-on experimentation. Home-based hands-on laboratory activities were performed in biology, electrical engineering, industrial engineering, transportation system, and civil engineering. The results of a Motivated Strategies for Learning Questionnaires (MLSQ) survey that was administered to about 100 STEM students revealed better gains in key constructs associated with student success, such as motivation, critical thinking, and metacognition.more » « less
-
This research is focused on the adoption of an experiment-centric teaching approach to enhance student’s learning, develop their critical thinking skills, and help students better understand the underlying concepts in biology, thereby giving them a better comprehension of how these concepts may be applied in practice as well as facilitating their academic success. Traditional and experiment-centric teaching methods are used to instruct students in four biology courses (BIO 101-W09 Introductory Biology for Non-Major, Bio 103 Introductory Biology for Nursing Major, BIO 109-001 Foundations in Biology, Diversity, and Organismal Systems and Bio 201. Anatomy and Physiology I) taken by first and second-year students. The sensor from a heart rate app is used to conduct and monitor several common experiments in Biology. On phone screens, the data gathered from these experiments can be visualized in real-time. In order to measure the key constructs associated with students’ success (motivation, epistemic and perceptual curiosity, and self-efficacy), data collection was done pre-and post-implementation of the experiments using the Motivated Strategies for Learning Questionnaire (MSLQ) developed by Pintrich, Smith, García, and McKeachie, in 1991. Also, the Classroom Observation Protocol for Undergraduate STEM (COPUS) was employed to characterize the simultaneous activities of instructors and learners during class sessions. More so, students’ understanding of the course and how they process instructions were evaluated using signature assignments. Data analysis would be conducted using Statistical Package for Social Scientists (SPSS 25.0). This research would carefully investigate the association between students’ motivation and their gender at 95% confidence level.more » « less
-
Nehm, Ross (Ed.)Students’ beliefs about their abilities (called “lay theories”) affect their motivations, behaviors, and academic success. Lay theories include beliefs about the potential to improve intelligence (mindset), who (i.e., everyone or only some people) has the potential to be excellent in a field (universality), and whether reaching excellence in a field requires raw intellectual talent (brilliance). Research demonstrates that each of these beliefs influences students’ educational experiences and academic outcomes. However, it remains unclear whether they represent distinct latent constructs or are susceptible to the “jangle fallacy” (i.e., different names given to the same underlying construct). We conducted a multiphase, mixed-methods study to 1) evaluate whether mindset, universality, and brilliance beliefs represent conceptually and empirically discriminable concepts, and 2) evaluate whether mindset, universality, and brilliance beliefs contribute unique explanatory value for both psychosocial (e.g., sense of belonging) and academic outcomes (e.g., course grades). To address these questions, we developed and collected validity evidence for a new measure of science and math undergraduates’ lay theories, called the Undergraduate Lay Theories of Abilities (ULTrA) survey. Factor analyses suggest that mindset, brilliance, and universality are distinct and empirically discriminable constructs. Structural Equation Models indicate that each lay theory contributes unique predictive value to relevant outcomes.more » « less
-
Abstract Background The ability to navigate obstacles and embrace iteration following failure is a hallmark of a scientific disposition and is hypothesized to increase students’ persistence in science, technology, engineering, and mathematics (STEM). However, this ability is often not explicitly explored or addressed by STEM instructors. Recent collective interest brought together STEM instructors, psychologists, and education researchers through the National Science Foundation (NSF) research collaborative Factors affecting Learning, Attitudes, and Mindsets in Education network (FLAMEnet) to investigate intrapersonal elements (e.g., individual differences, affect, motivation) that may influence students’ STEM persistence. One such element is fear of failure (FF), a complex interplay of emotion and cognition occurring when a student believes they may not be able to meet the needs of an achievement context. A validated measure for assessing FF, the Performance Failure Appraisal Inventory (PFAI) exists in the psychological literature. However, this measure was validated in community, athletic, and general undergraduate samples, which may not accurately reflect the motivations, experiences, and diversity of undergraduate STEM students. Given the potential role of FF in STEM student persistence and motivation, we felt it important to determine if this measure accurately assessed FF for STEM undergraduates, and if not, how we could improve upon or adapt it for this purpose. Results Using exploratory and confirmatory factor analysis and cognitive interviews, we re-validated the PFAI with a sample of undergraduates enrolled in STEM courses, primarily introductory biology and chemistry. Results indicate that a modified 15-item four-factor structure is more appropriate for assessing levels of FF in STEM students, particularly among those from groups underrepresented in STEM. Conclusions In addition to presenting an alternate factor structure, our data suggest that using the original form of the PFAI measure may significantly misrepresent levels of FF in the STEM context. This paper details our collaborative validation process and discusses implications of the results for choosing, using, and interpreting psychological assessment tools within STEM undergraduate populations.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1037/edu0000803
