Année : 2019
Lieu de publication de l'article :

Résumé de l'article

Learning Analytics Dashboards (LADs) are predicated on the no-tion that access to more academic information can help studentsregulate their academic behaviors, but what is the association be-tween information seeking preferences and help-seeking practicesamong college students? If given access to more information, whatmight college students do with it?We investigated these questions in a series of two studies. Study1 validates a measure of information-seeking preferences—the Mo-tivated Information-Seeking Questionnaire (MISQ)—-using a col-lege student sample drawn from across the country (n = 551). Ina second study, we used the MISQ to measure college students’(n=210) performance-avoid (i.e., avoiding seeming incompetent inrelation to one’s peers) and performance-approach (i.e., wishingto outperform one’s peers) information seeking preferences, theirhelp-seeking behaviors, and their ability to comprehend line graphsand bar graphs—two common graphs types for LADs.Results point to a negative relationship between graph compre-hension and help-seeking strategies, such as attending office hours,emailing one’s professor for help, or visiting a study center—evenafter controlling for academic performance and demographic char-acteristics. This suggests that students more capable of readingsgraphs might not seek help when needed. Further results suggest apositive relationship between performance-approach information-seeking preferences, and how often students compare themselvesto their peers.This study contributes to our understanding of the motivationalimplications of academic data visualizations in academic settings,and increases our knowledge of the way students interpret visu-alizations. It uncovers tensions between what students want tosee, versus what it might be more motivationally appropriate forthem to see. Importantly, the MISQ and graph comprehension mea-sure can be used in future studies to better understand the roleof students’ information seeking tendencies with regard to theirinterpretation of various kinds of feedback present in LADs.Permission to make digital or hard copies of all or part of this work for personal orclassroom use is granted without fee provided that copies are not made or distributedfor profit or commercial advantage and that copies bear this notice and the full citationon the first page. Copyrights for components of this work owned by others than theauthor(s) must be honored. Abstracting with credit is permitted. To copy otherwise, orrepublish, to post on servers or to redistribute to lists, requires prior specific permissionand/or a fee. Request permissions from permissions@acm.org.LAK19, March 4–8, 2019, Tempe, AZ, USA© 2019 Copyright held by the owner/author(s). Publication rights licensed to Associa-tion for Computing Machinery.ACM ISBN 978-1-4503-6256-6/19/03. . . $15.00https://doi.org/10.1145/3303772.3303805CCS CONCEPTS•Human-centered computing→ Information visualization;KEYWORDSMotivation, Non-cognitive factors, Instrument Validation, Visual-izations, Higher EducationACM Reference Format:Stephen J. Aguilar and Clare Baek. 2019. Motivated Information Seekingand Graph Comprehension Among College Students. In The 9th Interna-tional Learning Analytics Knowledge Conference (LAK19), March 4–8, 2019,Tempe, AZ, USA. ACM, New York, NY, USA, 10 pages. https://doi.org/10.1145/3303772.3303805

Mots-clés

List comprehension,Information seeking,Management Information Systems Quarterly,Data visualization,Futures studies,