Measuring university students’ interest in biology: evaluation of an instrument targeting Hidi and Renninger’s individual interest

Knekta, Eva; Rowland, Ashley A.; Corwin, Lisa A.; Eddy, Sarah L.

doi:10.1186/s40594-020-00217-4

Cited by 22 publications

(15 citation statements)

References 52 publications

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“…Further, only 2 studies used instruments with evidence of validity. However, that trend may change as there are more examples of instruments with evidence of validity, such as the Student Response to Instructional Practices (StRIP, DeMonbrun et al, 2017), the Biology Interest Questionnaire (BIQ, Knekta, Rowland, Corwin, & Eddy, 2020), and the Pedagogical Expectancy Violation Assessment (PEVA, Gaffney et al, 2010).…”

Section: Research Design Methods and Outcomesmentioning

confidence: 99%

Instructor strategies to aid implementation of active learning: a systematic literature review

et al. 2021

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Background Despite the evidence supporting the effectiveness of active learning in undergraduate STEM courses, the adoption of active learning has been slow. One barrier to adoption is instructors’ concerns about students’ affective and behavioral responses to active learning, especially student resistance. Numerous education researchers have documented their use of active learning in STEM classrooms. However, there is no research yet that systematically analyzes these studies for strategies to aid implementation of active learning and address students’ affective and behavioral responses. In this paper, we conduct a systematic literature review and identify 29 journal articles and conference papers that researched active learning, affective and behavioral student responses, and recommended at least one strategy for implementing active learning. In this paper, we ask: (1) What are the characteristics of studies that examine affective and behavioral outcomes of active learning and provide instructor strategies? (2) What instructor strategies to aid implementation of active learning do the authors of these studies provide? Results In our review, we noted that most active learning activities involved in-class problem solving within a traditional lecture-based course (N = 21). We found mostly positive affective and behavioral outcomes for students’ self-reports of learning, participation in the activities, and course satisfaction (N = 23). From our analysis of the 29 studies, we identified eight strategies to aid implementation of active learning based on three categories. Explanation strategies included providing students with clarifications and reasons for using active learning. Facilitation strategies entailed working with students and ensuring that the activity functions as intended. Planning strategies involved working outside of the class to improve the active learning experience. Conclusion To increase the adoption of active learning and address students’ responses to active learning, this study provides strategies to support instructors. The eight strategies are listed with evidence from numerous studies within our review on affective and behavioral responses to active learning. Future work should examine instructor strategies and their connection with other affective outcomes, such as identity, interests, and emotions.

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Section: Research Design Methods and Outcomesmentioning

confidence: 99%

Instructor strategies to aid implementation of active learning: a systematic literature review

et al. 2021

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“…Future research should also investigate assessment of other intrapersonal elements, such as coping style and sense of belonging, that could be context-dependent and may require careful consideration of the population of interest. It is clear from this work and others (e.g., Knekta et al 2019;Knekta et al 2020;Rowland et al 2019) that considering how to accurately assess these complex elements in STEM contexts may be imperative to gain an understanding of their roles in influencing student outcomes. Currently, there is a paucity of instruments available to measure intrapersonal elements in STEM contexts (Henry et al 2019) and more generally a need to improve the quality of measurements for latent variables in STEM populations (Knekta et al 2019;Limeri et al 2020;Rowland et al 2019).…”

Section: Discussionmentioning

confidence: 98%

Quantifying fear of failure in STEM: modifying and evaluating the Performance Failure Appraisal Inventory (PFAI) for use with STEM undergraduates

et al. 2021

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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.

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“…A. Renninger and S. Hidi's methodology (KNEKTA et al, 2020). Scientists distinguish four phases: the first phase is triggering situational interest, the second phase is keeping situational interest, the third phase corresponds to the emerging individual interest, and the fourth phase is a well-developed individual interest.…”

Section: Literature Reviewmentioning

confidence: 99%

Cognitive interest as a key indicator of adolescent personality development

Rymanova

Savvina

Safronova

et al. 2021

Laplage

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The research objective is to show new possibilities for understanding cognitive interest as one of the indicators of personality development. Based on a systematic analysis, the authors clarified the content of the category of “cognitive interest”. A conceptual model of the dialectic of interest in knowledge was proposed. The principles that are the foundation of the process of its learning were revealed. On this ground, educational technology was developed. Long-term observations of the subjects of the educational process, conducted by the authors, allowed determining the dialectical connections of cognitive interest with thinking, attention, memory, speech, and emotions. The pro-posed model of the dialectic of interest in knowledge is conceptual, since based on it, the process of raising interest is built as a didactically thought-out system for managing children’s development, contributing to their personal growth, one of the components of which is educational technology.

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Measuring university students’ interest in biology: evaluation of an instrument targeting Hidi and Renninger’s individual interest

Cited by 22 publications

References 52 publications

Instructor strategies to aid implementation of active learning: a systematic literature review

Instructor strategies to aid implementation of active learning: a systematic literature review

Quantifying fear of failure in STEM: modifying and evaluating the Performance Failure Appraisal Inventory (PFAI) for use with STEM undergraduates

Cognitive interest as a key indicator of adolescent personality development

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