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Three learning curves showing different learning rates. Note: the dashed line indicates performance when the number of hours spent studying is equal to eight. The vertical separation between the curves is not stable over the amount of time spent studying, meaning that shifting the curve’s slope would have heterogeneous effects dependent on the learner’s number of hours spent studying

Three learning curves showing different learning rates. Note: the dashed line indicates performance when the number of hours spent studying is equal to eight. The vertical separation between the curves is not stable over the amount of time spent studying, meaning that shifting the curve’s slope would have heterogeneous effects dependent on the learner’s number of hours spent studying

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The computational model of school achievement represents a novel approach to theorizing school achievement, conceptualizing educational interventions as modifications to students’ learning curves. By modeling the process and products of educational achievement simultaneously, this tool addresses several unresolved questions in educational psycholog...

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... 17). This view that theories often cannot be tested directly reflects a certain perspective which, in its most extreme form, may be questioned or even refuted by advocates for formal theories and computational modeling (Grahek et al., 2021;Schuetze, 2024). However, what we found thought-provoking is that Barzilai and Chinn's comment suggests that fully realizing the virtue of practicality in particular, but to some extent also the virtues of fruitfulness, accuracy, and testability, may be facilitated when theorists do this work of bridging theory to practice in research as well as in education. ...
... These posited mechanisms generate specific hypotheses that can be formalized and tested, leading to stronger tests of the theories and more actionable implications for education and practice (Robinaugh et al., 2021;van Dongen et al., 2024). Formalized theories and computational models are promising ways to make educational psychology theories more testable and also more translatable to practice, and we look forward to new generations of educational psychologists trained to formalize, and thus productively develop, existing theories (e.g., Schuetze, 2024). ...
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Throughout 2023 and 2024, we served as co-guest editors of a topical collection in Educational Psychology Review on The Past, Present, and Future of Theory Development in Educational Psychology. In this topical collection, authors of prominent theories in the field were invited to reflect upon how they generated, developed, and iterated their ideas, as well as what the future might hold for their theories. Our hope was these articles could serve as examples of how theory building happens, normalizations of the often difficult and circuitous paths theories can take from initial observations to formalizations, and inspirations to others to begin their own theory development journey. In this reflection on the topical collection, we present themes that emerged as we curated the articles, including themes we anticipated (e.g., the many different ways theories can be generated) as well as ones we did not (e.g., the mix of boldness and intellectual humility theory generation requires). Also, we examine the epistemic virtues our authors used to evaluate their theories, such as practicality, as well as the virtues that were less commonly mentioned, such as internal consistency. Finally, we identify future directions for theory development in educational psychology, including the need to improve the climate for theory development in the field, particularly in terms of creating structures that incentivize and reward natural history work.
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Though we see the potential for benefits from the development of process-oriented approaches, we argue that it falls prey to many of the same critiques raised about the existing construct level of analysis. The construct-level approach will likely dominate motivation research until we develop computational models that are not only accurate, but also broadly usable.