Cited by 55

Applying learning analytics dashboards based on process‐oriented feedback to improve students' learning effectiveness

Wang, Dongqing, Han, Hou·2021·Journal of Computer Assisted Learning

Abstract

With the development of a technology‐supported environment, it is plausible to provide rich process‐oriented feedback in a timely manner. In this paper, we developed a learning analytics dashboard (LAD) based on process‐oriented feedback in iTutor to offer learners their final scores, sub‐scale reports, and corresponding suggestions on further learning content. We adopted a quasi‐experimental design to investigate the effectiveness of the report on students' learning. Ninety‐four freshman from two classes participated in this research. The two classes were divided into the LAD group and the original analytics report (OAR) based on a product‐oriented feedback group. Before the experiment, all the students took the prior knowledge assessment. After a semester's instruction, all the students took the post‐test of the summative assessment. Results indicated that students in the LAD group experienced better learning effectiveness than students in the OAR group. LAD based on process‐oriented feedback was also effective in improving the skill learning effectiveness of the students with low‐level prior knowledge.

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1111/jcal.12502

Cites

11 of 11 references verified0 citation errors · 0 not checkable

Statistics

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Authors
Wang, D., & Han, H.
Venue
Journal of Computer Assisted Learning
Publisher
Wiley
Published
2020-10-26
Volume
37
Issue
2
Pages
487-499
ISSN
  • 0266-4909
  • 1365-2729
Cited by
55
References
11
Language
en

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review