The process of using analytic data to inform instructional decision-making is acknowledged to be complex; however, details of how it occurs in authentic teaching contexts have not been fully unpacked. This study investigated five university instructors’ use of a learning analytics dashboard to inform their teaching. The existing literature was synthesized to create a template for inquiry that guided interviews, and inductive qualitative analysis was used to identify salient emergent themes in how instructors 1) asked questions, 2) interpreted data, 3) took action, and 4) checked impact. Findings showed that instructors did not always come to analytics use with specific questions, but rather with general areas of curiosity. Questions additionally emerged and were refined through interaction with the analytics. Data interpretation involved two distinct activities, often along with affective reactions to data: reading data toidentify noteworthy patterns and explaining their importance in the course using contextual knowledge. Pedagogical responses to the analytics included whole-class scaffolding, targeted scaffolding, and revising course design, as well two new non-action responses: adopting a wait-and-see posture and engaging in deep reflection on pedagogy. Findings were synthesized into a model of instructor analytics use that offers useful categories of activities for future study and support
29 September 2025 in Interactive Learning Environments
The purpose of this study was to develop team projects in design thinking, for promotion and examination with the cultivation of group creativity. Research was conducted during the spring of 2017, with sixteen graduate students. Using artifact-based interviews, we analyzed the development of group creativity during the five stages of design thinking: understanding knowledge, empathizing, sharing perspectives, generating ideas, and prototyping. Results showed that analytical thinking was present throughout the overall project, while factors related to group creativity (such as learner orientation, interpersonal understanding, and flexibility) were observed at different rates as the project progressed. Results suggest that such pedagogical strategies as idea checking and training for applicability are necessary in order to foster group creativity.
7 February 2025 in Journal of Computing in Higher Education
This study fills a gap in knowledge regarding experienced instructors’ use of learning analytics, focusing on differences in their approach, the knowledge and skills they activate, and the development of these knowledge and skills. Through a qualitative analysis of think-aloud interviews with 13 analytics-experienced instructors, two distinct profiles of analytics use emerged. Instructors in the first profile prioritized monitoring student engagement and performance to foster desirable behaviors, using analytics to align students with course expectations. Instructors in the second profile focused on understanding student perceptions of learning, aligning the course design with diverse learning behaviors and needs. To arrive at such use, instructors went beyond mere acquisition of technical knowledge to also integrate pedagogical knowledge into their analytics practices. Lastly, the study uncovered specific learning analytics supports, such as ongoing individual consultations, invaluable for developing the needed technical and pedagogical knowledge. Together, the results of this study reveal the pivotal role of pedagogy in analytics use, calling for refinement of conceptual models and tailoring of practical support for instructors.