TY - JOUR
T1 - Exploring jump back behavior patterns and reasons in e-book system
AU - Ma, Boxuan
AU - Lu, Min
AU - Taniguchi, Yuta
AU - Konomi, Shin’ichi
N1 - Funding Information:
This work was supported by JSPS KAKENHI Grant Nos. JP16H06304, JP20H00622, JP20K19939.
Publisher Copyright:
© 2021, The Author(s).
PY - 2022/12
Y1 - 2022/12
N2 - With the increasing use of digital learning materials in higher education, the accumulated operational log data provide a unique opportunity to analyzing student learning behaviors and their effects on student learning performance to understand how students learn with e-books. Among the students’ reading behaviors interacting with e-book systems, we find that jump-back is a frequent and informative behavior type. In this paper, we aim to understand the student’s intention for a jump-back using user learning log data on the e-book materials of a course in our university. We at first formally define the “jump-back” behaviors that can be detected from the click event stream of slide reading and then systematically study the behaviors from different perspectives on the e-book event stream data. Finally, by sampling 22 learning materials, we identify six reading activity patterns that can explain jump backs. Our analysis provides an approach to enriching the understanding of e-book learning behaviors and informs design implications for e-book systems.
AB - With the increasing use of digital learning materials in higher education, the accumulated operational log data provide a unique opportunity to analyzing student learning behaviors and their effects on student learning performance to understand how students learn with e-books. Among the students’ reading behaviors interacting with e-book systems, we find that jump-back is a frequent and informative behavior type. In this paper, we aim to understand the student’s intention for a jump-back using user learning log data on the e-book materials of a course in our university. We at first formally define the “jump-back” behaviors that can be detected from the click event stream of slide reading and then systematically study the behaviors from different perspectives on the e-book event stream data. Finally, by sampling 22 learning materials, we identify six reading activity patterns that can explain jump backs. Our analysis provides an approach to enriching the understanding of e-book learning behaviors and informs design implications for e-book systems.
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U2 - 10.1186/s40561-021-00183-6
DO - 10.1186/s40561-021-00183-6
M3 - Article
AN - SCOPUS:85122287977
SN - 2196-7091
VL - 9
JO - Smart Learning Environments
JF - Smart Learning Environments
IS - 1
M1 - 2
ER -