How might faculty use the emerging field of learning analytics to inform their teaching practice or course design? Consider an interdisciplinary research project at Indiana University that studied the analytics of student “grade surprise” across five, very large (300+ students), general education courses enrolling just over 6,000 students. According to principal investigator Jennifer Meta Robinson, most IU freshmen graduate in the top 10% of their high school classes. Yet nearly 40% of the study’s student sample were “surprised” or “very surprised” by the grade on their first major assignment in their first term at IU.
“Our preliminary study shows that IU students in their first year are likely to experience grade surprise that could derail their plans for a major and their progress to graduation,” Robinson said in an IU news release about the study receiving a $20k AAU mini-grant. “We plan to develop strategies for both teaching and learning that will lessen the detrimental impact that can come with grade surprise.” Among other things, Robinson and her colleagues found the actual survey of students’ expectations about their final grades—early in course and term—may serve as a metacognitive intervention or “nudge” in its own right.Robinson, who is a professor of the practice in Anthropology and co-director of the Graduate Certificate on College Pedagogy, and joined with other IU colleagues as IU Learning Analytics Fellows to pursue the “Grade Surprise” project, will give a virtual “brown bag” presentation on Thursday, March 11, at noon. At 1 p.m., she’ll be joined by George Rehrey, founding director of IU's Center for Learning Analytics and Student Success (CLASS), who organizes IU’s annual Learning Analytics Summit and runs the LA Fellows program, for an informal chat to share lessons learned since the program began in 2016.