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1. Clustering learners’ feedback processing patterns based on their response latency

   Chu, W.; Pavlik jr., P.I. (July 2022, Proceedings of The Third Workshop of the Learner Data Institute , The 15th International Conference on Educational Data Mining (EDM 2022))

   In intelligent tutoring systems (ITS) abundant supportive messages are provided to learners. One implicit assumption behind this design is that learners would actively process and benefit from feedback messages when interacting with ITS individually. However, this is not true for all learners; some gain little after numerous practice opportunities. In the current research, we assume that if the learner invests enough cognitive effort to review feedback messages provided by the system, the learner’s performance should be improved as practice opportunities accumulate. We expect that the learner’s cognitive effort investment could be reflected to some extent by the response latency, then the learner’s improvement should also be correlated with the response latency. Therefore, based on this core hypothesis, we conduct a cluster analysis by exploring features relevant to learners’ response latency. We expect to find several features that could be used as indicators of the feedback usage of learners; consequently, these features may be used to predict learners’ learning gain in future research. Our results suggest that learners’ prior knowledge level plays a role when interacting with ITS and different patterns of response latency. Learners with higher prior knowledge levels tend to interact flexibly with the system and use feedback messages more effectively. The quality of their previous attempts influences their response latency. However, learners with lower prior knowledge perform two opposite patterns, some tend to respond more quickly, and some tend to respond more slowly. One common characteristic of these learners is their incorrect response latency is not influenced by the quality of their previous performance. One interesting result is that those quick responders forget faster. Thus, we concluded that for learners with lower prior knowledge, it is better for them not to react hastily to obtain a more durable memory. 

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2. The Curious Construct of Active Learning

   https://doi.org/10.1177/1529100620973974  

   Lombardi, Doug; Shipley, Thomas F.; Bailey, Janelle M.; Bretones, Paulo S.; Prather, Edward E.; Ballen, Cissy J.; Knight, Jennifer K.; Smith, Michelle K.; Stowe, Ryan L.; Cooper, Melanie M.; et al (April 2021, Psychological Science in the Public Interest)

   null (Ed.)

   The construct of active learning permeates undergraduate education in science, technology, engineering, and mathematics (STEM), but despite its prevalence, the construct means different things to different people, groups, and STEM domains. To better understand active learning, we constructed this review through an innovative interdisciplinary collaboration involving research teams from psychology and discipline-based education research (DBER). Our collaboration examined active learning from two different perspectives (i.e., psychology and DBER) and surveyed the current landscape of undergraduate STEM instructional practices related to the modes of active learning and traditional lecture. On that basis, we concluded that active learning—which is commonly used to communicate an alternative to lecture and does serve a purpose in higher education classroom practice—is an umbrella term that is not particularly useful in advancing research on learning. To clarify, we synthesized a working definition of active learning that operates within an elaborative framework, which we call the construction-of-understanding ecosystem. A cornerstone of this framework is that undergraduate learners should be active agents during instruction and that the social construction of meaning plays an important role for many learners, above and beyond their individual cognitive construction of knowledge. Our proposed framework offers a coherent and actionable concept of active learning with the aim of advancing future research and practice in undergraduate STEM education. 

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3. ON THE SOCIAL AND COGNITIVE DIMENSIONS OF WICKED ENVIRONMENTAL PROBLEMS CHARACTERIZED BY CONCEPTUAL AND SOLUTION UNCERTAINTY

   https://doi.org/10.1142/S0219525921500053  

   ARROYAVE, FELBER J.; GOYENECHE, OSCAR YANDY; GORE, MEREDITH; HEIMERIKS, GASTON; JENKINS, JEFFREY; PETERSEN, ALEXANDER M. (June 2021, Advances in Complex Systems)

   We develop a quantitative framework for understanding the class of wicked problems that emerge at the intersections of natural, social, and technological complex systems. Wicked problems reflect our incomplete understanding of interdependent global systems and the systemic risk they pose; such problems escape solutions because they are often ill-defined, and thus mis-identified and under-appreciated by communities of problem-solvers. While there are well-documented benefits to tackling boundary-crossing problems from various viewpoints, the integration of diverse approaches can nevertheless contribute confusion around the collective understanding of the core concepts and feasible solutions. We explore this paradox by analyzing the development of both scholarly (social) and topical (cognitive) communities — two facets of knowledge production studies here that contribute towards the evolution of knowledge in and around a problem, termed a knowledge trajectory — associated with three wicked problems: deforestation, invasive species, and wildlife trade. We posit that saturation in the dynamics of social and cognitive diversity growth is an indicator of reduced uncertainty in the evolution of the comprehensive knowledge trajectory emerging around each wicked problem. Informed by comprehensive bibliometric data capturing both social and cognitive dimensions of each problem domain, we thereby develop a framework that assesses the stability of knowledge trajectory dynamics as an indicator of wickedness associated with conceptual and solution uncertainty. As such, our results identify wildlife trade as a wicked problem that may be difficult to address given recent instability in its knowledge trajectory. 

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4. Investigating the Relations between Students' Affective States and the Coherence in their Activities in Open-Ended Learning Environments

   https://doi.org/10.5281/zenodo.12729872  

   Akpanoko, Celestine E; S, Ashwin T; Cordell, Grayson; Biswas, Gautam (January 2024, International Educational Data Mining Society)

   Benjamin, Paaßen; Carrie, Demmans Epp (Ed.)

   Open-ended learning environments (OELEs) have become an important tool for promoting constructivist STEM learning. OELEs are known to promote student engagement and facilitate a deeper understanding of STEM topics. Despite their benefits, OELEs present significant challenges to novice learners who may lack the self-regulated learning (SRL) processes they need to become effective learners and problem solvers. Recent studies have revealed the importance of the relationship between students' affective states, cognitive processes, and performance in OELEs. Yet, the relations between students' use of cognitive processes and their corresponding affective states have not been studied in detail. In this paper, we investigate the relations between studentsż˝f affective states and the coherence in their cognitive strategies as they work on developing causal models of scientific processes in the XYZ OELE. Our analyses and results demonstrate that there are significant differences in the coherence of cognitive strategies used by high- and low-performing students. As a result, there are also significant differences in the affective states of the high- and low-performing students that are related to the coherence of their cognitive activities. This research contributes valuable empirical evidence on studentsż˝f cognitive-affective dynamics in OELEs, emphasizing the subtle ways in which students' understanding of their cognitive processes impacts their emotional reactions in learning environments. 

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5. The Multi-method Comprehensive Review: Synthesis and Analysis when Scholarship is International, Interdisciplinary, and Immense

   https://doi.org/doi.org/10.1007/s11266-021-00388-w  

   Allison Schnable, Anthony J. (October 2021, Voluntas)

   This article presents a new strategy for reviewing large, multidisciplinary academic literatures: a multi-method comprehensive review (MCR). We present this approach and demonstrate its use by the NGO Knowledge Collective, which aims to aggregate knowledge on NGOs in international development. We explain the process by which scholars can identify, analyze, and synthesize a population of hundreds or thousands of articles. MCRs facilitate cross-disciplinary synthesis, systematically identify gaps in a literature, and can create data for further scholarly use. The main drawback is the significant resources needed to manage the volume of text to review, although such obstacles may be mitigated through advances in “big data” methodologies over time. 

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