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ERIC Number: ED596576
Record Type: Non-Journal
Publication Date: 2017-Jun
Pages: 6
Abstractor: As Provided
Gaze-Based Detection of Mind Wandering during Lecture Viewing
Hutt, Stephen; Hardey, Jessica; Bixler, Robert; Stewart, Angela; Risko, Evan; D'Mello, Sidney K.
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (10th, Wuhan, China, Jun 25-28, 2017)
We investigate the use of consumer-grade eye tracking to automatically detect Mind Wandering (MW) during learning from a recorded lecture, a key component of many Massive Open Online Courses (MOOCs). We considered two feature sets: stimulus-independent global gaze features (e.g., number of fixations, fixation duration), and stimulus-dependent local features. We trained Bayesian networks using the aforementioned features and students? self-reports of MW and validated them in a manner that generalized to new students. Our results indicated that models built with global features (F[subscript 1] MW = 0.47) outperformed those using local features (F[subscript 1] MW = 0.34) and a chance-level model (F[subscript 1] MW = 0.30). We discuss our results in the context of MOOC development as well as integrating MW detection into attention-aware MOOCs. [For the full proceedings, see ED596512.]
International Educational Data Mining Society. e-mail:; Web site:
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF)
Authoring Institution: N/A
Identifiers - Location: Canada
Grant or Contract Numbers: DRL1235958; IIS1523091