Browsing by Author "Hook, Sara"

Now showing 1 - 3 of 3
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    Impact of SoTL on Online and Face-to-Face Courses
    (2016-04-01) Hook, Sara; Liugen, Zhu
    Drawn from the literature and the experiences of two faculty members, this presentation will highlight the many opportunities to engage in SoTL and demonstrate the impact that SoTL activities have had on the teaching approaches and student learning outcomes that the presenters have seen in the diverse array of face-to-face and online courses that they teach.
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    Revising Program-Level Learning Outcomes: Methodology, Results and Lessons Learned
    (2018-04-06) Hook, Sara; Zhu, Liugen
    The presenters developed a methodology for revising program-level learning outcomes that is efficient, effective and readily adaptable for other degrees. They will introduce their methodology, present preliminary findings, identify what worked well versus how the methodology could be improved upon in the future and offer insights into how the methodology could be used to revise learning outcomes in other disciplines.
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    Sensemaking during the use of learning analytics in the context of a large college system
    (2017-04-05) Morse, Robert Kenneth; Brady, Erin; Bolchini, Davide; Boling, Elizabeth; Hook, Sara
    This research took place as a cognitive exploration of sensemaking of learning analytics at Ivy Tech Community College of Indiana. For the courses with the largest online enrollment, quality standards in the course design are maintained by creating sections from a course design framework. This means all sections have the same starting content and the same framework for assessment. The course design framework is maintained by the curriculum committee composed of program chairs who oversee the program to which the course belongs. This research proposed to develop a learning analytics dashboard to elicit the best practices in instantiating a course design framework from the perspective of the program chair. The Instructional Design Implementation Dashboard, IDID, was designed to address the sensemaking needs of program chairs. The program chairs were asked to make sense of IDID built around the data collected from the course management system and the student information system. IDID leveraged metrics from the user activity and the learner performance from the learning management system, combined with data about the student demographics captured from the student information system. IDID was used to identify highly successful sections and examine the instructor behaviors that might be considered best practices. Data Frame Sensemaking theory was confirmed as an accurate description of the experience of program chairs when using IDID. A revised model of Data Frame Sensemaking theory was developed to explain the interaction of those using the IDID platform.