Student-facing Learning AnalyticsWorkshop Discussion Examples

This slide deck contains a variety of screenshots of existing, potentially prototype, student-facingdashboards, or mockups of them. They are collected together as a resource for workshopdiscussion about different approaches and their relative desirability and effectiveness indifferent contexts, which might differ from those for which the example was originally designed.

Inclusion of a screenshot or mockup in this deck is not intended to indicate either negativecriticism or endorsement; the selection process used by the workshop organisers was based oncollecting examples showing a variety of approaches.

In the sense that this collection is a separate work, it is dedicated as CC0 (Public Domain),without prejudice to the copyright of the original software or mockup creators, which theworkshop organisers acknowledge.

For more information, about the workshop, please refer to:

https://sflaprinciples.wordpress.com/

Dashboard mock-up developed at OUNL to be used as an assignment in a Learning Analytics course. The purpose of the dashboard was tosupport learners in self-regulating their learning. Course participants were supposed to analyse and evaluate the dashboard as if thedashboard was showing their data: how they’d evaluate their performance, how they’d change their behaviour, what features they findmotivating and which demotivating and what else about their learning they’d like to see on the dashboard.

(Jivet, I., Scheffel, M., Specht, M., Drachsler, H.; work in progress)

A

Purdue signals

this is the tutor

facing version of

the dashboard

this is the student

facing version.

RAG rated to show

progress

B

Ulster’s Student facing Dashboard

Bartholemew (2018) Jisc Experts Key Note Birmingham

C

Nottingham Trent

UCISA. (2018). The Truth About Data and Analytics

D

Mockups created by Tribal to solicit user-group feedback on a student-facing feature in its

Student Insight product.

These do not indicate which features will actually be developed.

explains the stats

Could be oriented towards

student self-efficacy,

preparation for tutor

meetings, ...

explains the chart

E

Corrin, L., & de Barba, P. (2014). Exploring students’ interpretation of feedback delivered through learning analytics dashboards. In Proceedings of the ascilite 2014 conference (pp. 629-633).

F

Govaerts, S., Verbert, K., & Duval, E. (2011, December). Evaluating the student activity meter: two case studies. In International Conference on Web-Based Learning (pp. 188-197). Springer, Berlin, Heidelberg.

G

Guerra, J., Hosseini, R., Somyurek, S., & Brusilovsky, P. (2016, March). An intelligent interface for learning content: Combining an open learner model and social comparison to support self-regulated learning and engagement. In Proceedings of the 21st International Conference on Intelligent User Interfaces (pp. 152-163). ACM.

H

Tan, J. P. L., Yang, S., Koh, E., & Jonathan, C. (2016, April). Fostering 21st century literacies through a collaborative critical reading and learning analytics environment: user-perceived benefits and problematics. In Proceedings of the sixth international conference on learning analytics & knowledge (pp. 430-434). ACM.

I

Davis, D., Jivet, I., Kizilcec, R. F., Chen, G., Hauff, C., & Houben, G. J. (2017, March). Follow the successful crowd: raising MOOC completion rates through social comparison at scale. In Proceedings of the Seventh International Learning Analytics & Knowledge Conference (pp. 454-463). ACM.

J

Scheffel, M., Drachsler, H., de Kraker, J., Kreijns, K., Slootmaker, A., & Specht, M. (2017). Widget, widget

on the wall, am I performing well at all? IEEE Transactions on Learning Technologies, 10(1), 42-52.

K

From Jayaprakash, S. M., Laur, E. J. M., #237, Gandhi, P., & Mendhe, D. (2016).

L

M

Ruiz, S., Charleer, S., Urretavizcaya, M., Klerkx, J., Fernández-Castro, I., & Duval, E. (2016, April). Supporting learning by considering emotions: tracking and visualization a case study. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (pp. 254-263). ACM.

N

Bull, S., Ginon, B., Boscolo, C., & Johnson, M. (2016, April). Introduction of learning visualisations and metacognitive support in a persuadable open learner model. In Proceedings of the sixth international conference on learning analytics & knowledge (pp. 30-39). ACM.

O

Aljohani, N. R., & Davis, H. C. (2013, September). Learning Analytics and Formative Assessment to Provide Immediate Detailed Feedback Using a Student Centered Mobile Dashboard. In Proceedings of the 2013 Seventh International Conference on Next Generation Mobile Apps, Services and Technologies (pp. 262-267). IEEE Computer Society.

P

Tabuenca, B., Kalz, M., Drachsler, H., & Specht, M. (2015). Time will tell: The role of mobile learning analytics in self-regulated learning. Computers & Education, 89, 53-74.

Q

Beheshitha, S. S., Hatala, M., Gašević, D., & Joksimović, S. (2016, April). The role of achievement goal orientations when studying effect of learning analytics visualizations. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (pp. 54-63). ACM.

R

Beheshitha, S. S., Hatala, M., Gašević, D., & Joksimović, S. (2016, April). The role of achievement goal orientations when studying effect of learning analytics visualizations. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (pp. 54-63). ACM.

S

Beheshitha, S. S., Hatala, M., Gašević, D., & Joksimović, S. (2016, April). The role of achievement goal orientations when studying effect of learning analytics visualizations. In Proceedings of the Sixth International Conference on Learning Analytics & Knowledge (pp. 54-63). ACM.

T

U

Screenshots from the Learning Analytics Report Card demo site. The LARC tool is used as a teaching tool with students studying on the MSc Digital Education at the University of Edinburgh. Through interrogating their own data from the VLE they are asked to critically engage with issues around data and learning analytics.

See Knox, J. (2017). Data power in education: Exploring critical awareness with the ‘Learning Analytics Report Card’ (LARC). Television and New Media, vol 18, no. 8.