72634 |
Creator |
c9d52ef4a11ad1277436a89c20d0a5d4 |
72634 |
Creator |
17452a4d6573661e9aff8220d6982acc |
72634 |
Date |
2014-12-02 |
72634 |
Is Part Of |
repository |
72634 |
Is Part Of |
p4126c1218b67ed02137c530131543764 |
72634 |
abstract |
Emotions play a critical role in the learning and teaching process because learners’
feelings impact motivation, self-regulation and academic achievement. In this literature
review of 100+ studies, we identify approximately 100 different emotions that may
have a positive, negative or neutral impact on learners’ attitudes, behaviour and
cognition. In this review, we explore seven methods of data gathering approaches to
measure and understand emotions (i.e., content analysis, natural language processing,
behavioural indicators, quantitative instruments, qualitative approaches, well-being
word clouds, and intelligent tutoring systems). With increased affordances of technologies
to continuously measure emotions (e.g., facial and voice expressions with tablets
and smart phones), it might become feasible to monitor learners’ emotions on a real-time
basis in the near future. |
72634 |
authorList |
authors |
72634 |
issue |
2 |
72634 |
status |
peerReviewed |
72634 |
uri |
http://data.open.ac.uk/oro/document/1234614 |
72634 |
uri |
http://data.open.ac.uk/oro/document/1234615 |
72634 |
uri |
http://data.open.ac.uk/oro/document/1234616 |
72634 |
uri |
http://data.open.ac.uk/oro/document/1234617 |
72634 |
uri |
http://data.open.ac.uk/oro/document/1234618 |
72634 |
uri |
http://data.open.ac.uk/oro/document/1234619 |
72634 |
uri |
http://data.open.ac.uk/oro/document/1247076 |
72634 |
type |
Article |
72634 |
label |
Rienties, Bart and Alden, Bethany (2014). Emotions used in Learning Analytics:
a state-of-the-art review. LACE project. |
72634 |
Publisher |
ext-e6694303da93fd2edc75cc8fa3e99ebe |
72634 |
Title |
Emotions used in Learning Analytics: a state-of-the-art review |
72634 |
in dataset |
oro |