Self-Report is Indispensable to Assess Students’ Learning

Pekrun, Reinhard

doi:10.14786/flr.v8i3.637

Cited by 92 publications

(60 citation statements)

References 18 publications

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“…Not only do these empirical pieces suggest lateral development is possible, each starts to take us down this journey and provides evidence that these journeys are likely to be fruitful. From empirical multimethod studies (e.g., van Halen et al, 2020;Rogiers, et al 2020) to the theoretically-rich commentaries (Pekrun, 2020;van Meter, 2020;Winne, 2020;), this Special Issue suggests that self-report measures are a unique, valuable -and therefore irreplaceable -source of information about many critical aspects of the learning processes under study here. Clearly, the conclusions drawn from these analyses show that self-report remains critical in our understanding of learning and that educational researchers need to push harder for constant lateral innovation such as these.…”

Section: Lateral and Vertical Innovation: Both Are Criticalmentioning

confidence: 96%

“…In turn, the better participants are at responding to these types of measurements, the better the interpretations of these data will be. Pekrun (2020) makes the case for the importance of self-report data, and like Winne touches on what they are. Pekrun extends this discussion by focusing primarily on how to improve the validity of the score interpretations of self-report data.…”

Section: The Commentariesmentioning

confidence: 99%

“…While each of this Special Issue's articles addresses this question in some form, the syntheses of the three commentaries address it best. All three of these commentaries point out the need to clearly understand the core construct (e.g., Pekrun, 2020), the measurement itself (Winne, 2020), and the conditional nature of their use (Van Meter, 2020). It is critical that the interpretations of self-report data are situated within theoretical frameworks of the core constructs that are being measured.…”

Section: Implications Of the Special Issuementioning

confidence: 99%

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The Promise and Pitfalls of Self-report

Fryer

Dinsmore

2020

FLR

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As a prelude to this special issue on the promise and pitfalls of self-report, this article addresses three issues critical to its current and future use. The development of self-report is framed in Vertical (improvement) and Horizontal (diversification) terms, making clear the role of both paths for continued innovation. The ongoing centrality of research design and analysis in ensuring that self-reported data is employed effectively is reviewed. Finally, the synergistic use of multiple methods is discussed. This article concludes with an overview of the SI's contributions and a summary of the SI's answers to its three central questions: a) In what ways do self-report instruments reflect the conceptualizations of the constructs suggested in theory related to motivation or strategy use? b) How does the use of self-report constrain the analytical choices made with that self-report data? c) How do the interpretations of self-report data influence interpretations of study findings?

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Section: Lateral and Vertical Innovation: Both Are Criticalmentioning

confidence: 96%

Section: The Commentariesmentioning

confidence: 99%

Section: Implications Of the Special Issuementioning

confidence: 99%

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The Promise and Pitfalls of Self-report

Fryer

Dinsmore

2020

FLR

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“…This can be done by studying the subjective feelings/experience of the two constructs at the momentary level. The subjective feelings of a construct serve as the first gate to the mental state of it (Pekrun, 2020), and the assessment is relatively straightforward and uncontroversial: We can simply ask participants' feelings of curiosity and interest at a specific moment. Although this is just one aspect of the broad concepts of curiosity and interest, this is a way in which we can empirically examine the potential similarities and differences of curiosity and interest.…”

Section: Current Status On the Empirical Investigations About Curiosimentioning

confidence: 99%

“…First, most studies in the meta-analysis and our Study 2 and 3 assessed curiosity and interest using self-reported questionnaires. Although selfreport may be an indispensable way to access emotional state, affect evaluation, or cognitive appraisal (Pekrun, 2020), there are some inherited problems with self-report measures such as bias or inaccuracy. It is expected that in the future, behavioral as well as neuroscientific research would provide triangulation for self-reports (Hidi & Renninger, 2019).…”

Section: Limitations and Future Directionsmentioning

confidence: 99%

The Differences and Similarities between Curiosity and Interest: Meta-analysis and Network Analyses

Tang¹,

Renninger²,

Hidi³

et al. 2020

Preprint

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The relationships and differences between curiosity and interest have received considerable attention and discussions. Yet, most of the discussions so far draw from little direct empirical evidence. In this set of three studies, the relationship between curiosity and interest were examined. The first study was a meta-analysis that examined the Pearson correlations between scales that aimed to assess curiosity and those that aimed to assess interest. Based on 24 studies (31 effect sizes), we found that curiosity scales correlate with interest scales at a moderate level (r = .53), but have extremely high heterogeneity, suggesting that the relationship largely depends on how they are conceptualized. The second and third studies applied network analyses (i.e., co-occurrence analysis and correlation-based analysis) to data collected using experience sampling method, examining how the subjective feelings of curiosity and interest are related. Across two studies, we found consistently differences between the feelings associated with curiosity and those associated with interest. While the feeling of curiosity was closer to feelings of inquisitiveness and eagerness to know more, the feeling of interest was closer to positive affects such as enjoyment and happiness. Most importantly, an asymmetrical pattern was found in curiosity-interest co-occurrences: when the feeling of curiosity occurred, the co-occurrences of the feeling of interest were highly likely, but not vice versa. That is, when the feeling of interest occurred, the feeling of curiosity was less likely to co-occur. The theoretical and practical implications of our findings are discussed.

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Community college student perceptions of digital anatomy models as a curricular resource

Baptiste,

Abramovich

2024

Anatomical Sciences Ed

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Digital model platforms and applications are common in anatomy education and continue to grow in number, which suggests that educators and students find use for these tools despite the lack of widely accepted best practices. Consequently, it is a challenge for educators to mindfully integrate digital models into curriculum. This short‐term, longitudinal study investigated the effects of integrating a monoscopic digital model as a teaching tool during lectures on reproductive and endocrine anatomy as an intervention in a community college human anatomy and physiology course. Student use and perceptions of digital models were analyzed for correlation with the nature of the course content and the intervention (n = 92). Academic content significantly affected self‐reported student use (p < 0.001) as well as student perceived usefulness of the model (p = 0.02). These findings support the conjecture that digital anatomy models may be better for achieving certain specific learning goals opposed to all learning goals. Integration of digital models as an instructional method did not consistently influence student behavior but it made a difference in participant ability to recognize this technology outside of the lecture. Overall, participants had a positive perception of digital models, although they were not perceived as more important than all other curricular resources. Inclusion of monoscopic digital models for teaching anatomy should be considered by educators since teaching with digital models can demonstrate strengths and weaknesses for students within the context the of learning objectives, assisting students to make more informed decisions about effective learning tools.

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Self-Report is Indispensable to Assess Students’ Learning

Cited by 92 publications

References 18 publications

The Promise and Pitfalls of Self-report

The Promise and Pitfalls of Self-report

The Differences and Similarities between Curiosity and Interest: Meta-analysis and Network Analyses

Community college student perceptions of digital anatomy models as a curricular resource

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