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Creators/Authors contains: "Roscoe, Rod D."

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  1. Free, publicly-accessible full text available August 1, 2024
  2. Literacy assessment is essential for effective literacy instruction and training. However, traditional paper-based literacy assessments are typically decontextualized and may cause stress and anxiety for test takers. In contrast, serious games and game environments allow for the assessment of literacy in more authentic and engaging ways, which has some potential to increase the assessment’s validity and reliability. The primary objective of this study is to examine the feasibility of a novel approach for stealthily assessing literacy skills using games in an intelligent tutoring system (ITS) designed for reading comprehension strategy training. We investigated the degree to which learners’ game performance and enjoyment predicted their scores on standardized reading tests. Amazon Mechanical Turk participants (n = 211) played three games in iSTART and self-reported their level of game enjoyment after each game. Participants also completed the Gates–MacGinitie Reading Test (GMRT), which includes vocabulary knowledge and reading comprehension measures. The results indicated that participants’ performance in each game as well as the combined performance across all three games predicted their literacy skills. However, the relations between game enjoyment and literacy skills varied across games. These findings suggest the potential of leveraging serious games to assess students’ literacy skills and improve the adaptivity of game-based learning environments. 
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    Free, publicly-accessible full text available July 1, 2024
  3. Four "who-ristic" questions to ask yourself when designing artificially intelligent educational technologies that will actually benefit people. 
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    Free, publicly-accessible full text available March 1, 2024
  4. Free, publicly-accessible full text available July 3, 2024
  5. Researchers and educators have developed a variety of computer-based technologies intended to facilitate self-regulated learning (SRL), which refers to iterative learning processes wherein individuals set plans and goals, complete tasks, monitor their progress and outcomes, and adapt future efforts. This paper draws upon the SRL literature and related work to articulate two fundamental principles for designing SRL-promoting technologies: the Platform Principle and the Support Principle. The Platform Principle states that SRL-promoting technologies must incorporate clear platforms (i.e., tools and features) for engaging in planning, enacting, monitoring, and adapting. The Support Principle states that SRL-promoting technologies must include clear scaffolds for strategies, metacognition, motivation, and independence. These principles can be applied heuristically to formatively assess how and whether given learning technologies enable and scaffold self-regulation. More broadly, these assessments can empower educational technology creators and users to strategically design, communicate, and study technologies aligned with self-regulation. An exemplar application of the framework is presented using the PERvasive Learning System (PERLS) mobile SRL technology. 
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  6. The current study an empirical evaluation of the PERvasive Learning System (PERLS). PERLS is a mobile microlearning platform designed for learning anytime and anywhere, taking advantage of planned and unplanned time during a learner’s daily schedule to enhance and reinforce learning. Soldiers taking classes from the Sabalauski Air Assault School at Fort Campbell, KY were recruited. This evaluation compared the impact of PERLS on soldiers’ self-efficacy for their self-regulated learning ability. This evaluation found evidence of impact for the PERLS when implemented into classroom setting with soldiers that used PERLS indicating higher self-efficacy scores. 
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  7. Virtual reality (VR) has a high potential to facilitate education. However, the design of many VR learning applications was criticized for lacking the guidance of explicit and appropriate learning theories. To advance the use of VR in effective instruction, this study proposed a model that extended the cognitive-affective theory of learning with media (CATLM) into a VR learning context and evaluated this model using a structural equation modeling (SEM) approach. Undergraduate students ( n = 77) learned about the solar system in a VR environment over three sessions. Overall, the results supported the core principles and assumptions of CATLM in a VR context (CATLM-VR). In addition, the CATLM-VR model illustrated how immersive VR may impact learning. Specifically, immersion had an overall positive impact on user experience and motivation. However, the impact of immersion on cognitive load was uncertain, and that uncertainty made the final learning outcomes less predictable. Enhancing students’ motivation and cognitive engagement may more directly increase learning achievement than increasing the level of immersion and may be more universally applicable in VR instruction. 
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  8. Despite decades of effort to broaden participation in science, technology, engineering, and mathematics (STEM), many fields remain demographically skewed. Marginalized and minoritized people are still underrepresented in and underserved by the sciences. In this paper, the author considers the question, “How do we improve representation in STEM?” by reflecting on his own journey and themes such as imposter syndrome, decentering, meritocracy, and activism. Importantly, “underrepresentation” is not a mysterious happenstance but rather a predictable outcome of systemic inequity and systematic exclusion. By attending to the mechanisms of oppression, we can enact interventions that address root causes instead of symptoms. There are multiple ways that our research, teaching, and practice might change “the system” by making inclusion and equity the focus of our work, applying these principles to frame research questions and interpret findings, and adopting methods and practices that are inclusive and equitable. 
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  9. The present study examined the extent to which adaptive feedback and just-in-time writing strategy instruction improved the quality of high school students’ persuasive essays in the context of the Writing Pal (W-Pal). W-Pal is a technology-based writing tool that integrates automated writing evaluation into an intelligent tutoring system. Students wrote a pretest essay, engaged with W-Pal’s adaptive instruction over the course of four training sessions, and then completed a posttest essay. For each training session, W-Pal differentiated strategy instruction for each student based on specific weaknesses in the initial training essays prior to providing the opportunity to revise. The results indicated that essay quality improved overall from pretest to posttest with respect to holistic quality, as well as several specific dimensions of essay quality, particularly for students with lower literacy skills. Moreover, students’ scores on some of the training essays improved from the initial to revised version on the dimensions of essay quality that were targeted by instruction, whereas scores did not improve on the dimensions that were not targeted by instruction. Overall, the results suggest that W-Pal’s adaptive strategy instruction can improve the quality of students’ essays overall, as well as more specific dimensions of essay quality. 
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