Search for: All records

There is a growing interest in the research and use of automated feedback dashboards that display classroom analytics; yet little is known about the detailed processes instructors use to make sense of these tools, and to determine the impact on their teaching practices. This research was conducted at a public Midwestern university within the context of an automated classroom observation and feedback implementation project. Fifteen engineering instructors engaged in this research. The overarching goal was to investigate instructor teaching beliefs, pedagogical practices, and sensemaking processes regarding dashboard use. A grounded theory approach was used to identify categories related to instructor perceptions. Results revealed that instructor experiences inform both their present use of the dashboard and consequential future actions. A model is presented that illustrates categories included in instructor pre-use, use, and post-use of an automated feedback dashboard. An extension to this model is presented and accompanied by recommendations for a more effective future use of automated dashboards. The model’s practical implications inform both instructors and designers on effective design and use of dashboards, ultimately paving a way to improve pedagogical practices and instruction 

Abstract Computational analysis methods and machine learning techniques introduce innovative ways to capture classroom interactions and display data on analytics dashboards. Automated classroom analytics employ advanced data analysis, providing educators with comprehensive insights into student participation, engagement, and behavioral trends within classroom settings. Through the provision of context-sensitive feedback, automated classroom analytics systems can be integrated into the evidence-based pedagogical decision-making and reflective practice processes of faculty members in higher education institutions. This paper presents TEACHActive, an automated classroom analytics system, by detailing its design and implementation. It outlines the processes of stakeholder engagement and mapping, elucidates the benefits and obstacles associated with a comprehensive classroom analytics system design, and concludes by discussing significant implications. These implications propose user-centric design approaches for higher education researchers and practitioners to consider. 

By 2028, the U.S. will have the largest percentage of foreign-born individuals since 1850 with non-Hispanic whites in the 18-29 age group in the minority. These changing demographics require a major shift in education practices that will affect these residents' ability to continue their education, recruit for civilian careers, enlist in the military, and simply navigate in a digital society. These residents have a range of challenges from language barriers to lack of access to the Internet and mobile devices that must be addressed. Extended Reality (XR) technologies, interwoven with learning theories, offer solutions to these challenges. This paper presents a study of XR-enabled educational delivery models with the community of Storm Lake to enhance students’ aspirations for Science, Technology, Engineering, and Mathematics (STEM) careers. Storm Lake is a rural Iowa community with a large low-skilled workforce employed in the agroindustrial sector and a K-12 student population that is 64% English Language Learners and 85% students of color. The research began with co-design activities (formal process actively involving all stakeholders) with teachers, students, and families in the community without technology use. Analyzed study data showed that traditional technology development and deployment practices would not effectively educate or inspire students on their own. For example, providing teachers with XR devices creates a training burden to properly operate, often resulting in unused technology. Co-design activities, with place-based challenges in XR environments, were effective for students to learn STEM-related content. Co-design activities concluded in a three-day summer workshop for 10 high school students. At the workshop, students defined place- based challenge(s) in their community and implemented an XR technological solution in software and hardware. Assessments showed positive results from the students on several measures, including evidence that the workshop contributed to seven of the 10 applying to a university in a STEM major.