ERIC Number: ED560881
Record Type: Non-Journal
Publication Date: 2015-Jun
Pages: 4
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: N/A
Available Date: N/A
Breaking off Engagement: Readers' Disengagement as a Function of Reader and Text Characteristics
Goedecke, Patricia J.; Dong, Daqi; Shi, Genghu; Feng, Shi; Risko, Evan; Olney, Andrew M.; D'Mello, Sidney K.; Graesser, Arthur C.
International Educational Data Mining Society, Paper presented at the International Conference on Educational Data Mining (EDM) (8th, Madrid, Spain, Jun 26-29, 2015)
Engagement during reading can be measured by the amount of time readers invest in the reading process. It is hypothesized that disengagement is marked by a decrease in time investment as compared with the demands made on the reader by the text. In this study, self-paced reading times for screens of text were predicted by a text complexity score called formality; formality scores increase with cohesion, informational content/genre, syntactic complexity, and word abstractness as measured by the Coh-Metrix text-analysis program. Cognitive decoupling is defined as the difference between actual reading times and reading times predicted by text formality. Decoupling patterns were found to differ as a function of the serial position of the screens of text and the text genre (i.e., informational, persuasive, and narrative) but surprisingly not as a function of reader characteristics (reading speed and comprehension). This underscores the importance of mining text characteristics in addition to individual differences and task constraints in understanding engagement during reading. [For complete proceedings, see ED560503.]
Descriptors: Learner Engagement, Reader Text Relationship, Time, Predictor Variables, Scores, Cognitive Processes, Reading Materials, Difficulty Level, Comprehension, Student Characteristics, Undergraduate Students, Reading Comprehension, Literary Genres, Reading Rate
International Educational Data Mining Society. e-mail: admin@educationaldatamining.org; Web site: http://www.educationaldatamining.org
Publication Type: Speeches/Meeting Papers; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: National Science Foundation (NSF); Institute of Education Sciences (ED)
Authoring Institution: International Educational Data Mining Society
IES Funded: Yes
Grant or Contract Numbers: 1108845; R305C120001
Author Affiliations: N/A