![](bgc.png)
learning and sense-making of learning analytics in
higher education. The Internet and Higher Education,
47:100758.
Jivet, I., Scheffel, M., Specht, M., and Drachsler, H.
(2018). License to evaluate: Preparing learning an-
alytics dashboards for educational practice. In Pro-
ceedings of the 8th international conference on learn-
ing analytics and knowledge, pages 31–40.
Keshavarzi, M., Bidgoli, A., and Kellner, H. (2020).
V-dream: Immersive exploration of generative de-
sign solution space. In International Conference on
Human-Computer Interaction, pages 477–494.
Khan, S., Gunpinar, E., and Sener, B. (2019). Geny-
acht: An interactive generative design system for
computer-aided yacht hull design. Ocean Engineer-
ing, 191:106462.
Kintz, M., Kochanowski, M., and Koetter, F. (2017). Cre-
ating user-specific business process monitoring dash-
boards with a model-driven approach. In MODEL-
SWARD, pages 353–361.
Klein, G., Moon, B., and Hoffman, R. R. (2006). Mak-
ing sense of sensemaking 1: Alternative perspectives.
IEEE intelligent systems, 21(4):70–73.
Laugwitz, B., Held, T., and Schrepp, M. (2008). Construc-
tion and evaluation of a user experience questionnaire.
In Symposium of the Austrian HCI and usability engi-
neering group, pages 63–76. Springer.
Liu, Z., Nersessian, N., and Stasko, J. (2008). Distributed
cognition as a theoretical framework for information
visualization. IEEE transactions on visualization and
computer graphics, 14(6):1173–1180.
Mayer, B. and Weinreich, R. (2017). A dashboard for
microservice monitoring and management. In 2017
IEEE International Conference on Software Architec-
ture Workshops (ICSAW), pages 66–69. IEEE.
Meyer, J., Thomas, J., Diehl, S., Fisher, B., and Keim, D. A.
(2010). From visualization to visually enabled rea-
soning. In Dagstuhl Follow-Ups, volume 1. Schloss
Dagstuhl-Leibniz-Zentrum fuer Informatik.
Pirolli, P. and Card, S. (2005). The sensemaking process
and leverage points for analyst technology as identi-
fied through cognitive task analysis. In Proceedings
of international conference on intelligence analysis,
volume 5, pages 2–4. McLean, VA, USA.
Prieto-Alvarez, C. G., Martinez-Maldonado, R., and An-
derson, T. D. (2018). Co-designing learning analyt-
ics tools with learners. In Learning Analytics in the
Classroom, pages 93–110. Routledge.
Sadallah, M., Gilliot, J.-M., Iksal, S., Quelennec, K., Ver-
meulen, M., Neyssensas, L., Aubert, O., and Venant,
R. (2022). Designing lads that promote sensemak-
ing: A participatory tool. In Educating for a New Fu-
ture: Making Sense of Technology-Enhanced Learn-
ing Adoption: Proceedings of the 17th European Con-
ference on Technology Enhanced Learning, EC-TEL
2022, volume 13450 of Lecture Notes in Computer
Science, pages 587–593. Springer.
Santoso, H. B., Schrepp, M., Isal, R., Utomo, A. Y., and
Priyogi, B. (2016). Measuring user experience of the
student-centered e-learning environment. Journal of
Educators Online, 13(1):58–79.
Sarmiento, J. P. and Wise, A. F. (2022). Participatory and
co-design of learning analytics: An initial review of
the literature. In Proceedings of the 12th International
Learning Analytics and Knowledge Conference, pages
535–541.
Schrepp, M., Hinderks, A., and Thomaschewski, J. (2014).
Applying the user experience questionnaire (ueq) in
different evaluation scenarios. In International Con-
ference of Design, User Experience, and Usability,
pages 383–392. Springer.
Schulz, H.-J., Hadlak, S., and Schumann, H. (2011). The
design space of implicit hierarchy visualization: A
survey. IEEE Transactions on Visualization and Com-
puter Graphics, 17(4):393–411.
Schwendimann, B. A., Rodr
´
ıguez-Triana, M. J., Vozniuk,
A., Prieto, L. P., Boroujeni, M. S., Holzer, A., Gillet,
D., and Dillenbourg, P. (2017). Perceiving learning
at a glance: A systematic literature review of learning
dashboard research. IEEE Transactions on Learning
Technologies, 10(1):30–41.
Sedrakyan, G., Mannens, E., and Verbert, K. (2019). Guid-
ing the choice of learning dashboard visualizations:
Linking dashboard design and data visualization con-
cepts. Journal of Computer Languages, 50:19–38.
Shaw, M. (2012). The role of design spaces. IEEE software,
29(1):46–50.
Shneiderman, B. (2003). The eyes have it: A task by data
type taxonomy for information visualizations. In The
craft of information visualization, pages 364–371. El-
sevier.
Tullis, T. S. and Stetson, J. N. (2004). A comparison of
questionnaires for assessing website usability. In Us-
ability Professionals Association 2004 Conference.
Van Wijk, J. J. (2005). The value of visualization. In VIS
05. IEEE Visualization, 2005., pages 79–86. IEEE.
V
´
azquez-Ingelmo, A., Garcia-Penalvo, F. J., and Theron,
R. (2019). Information dashboards and tailoring
capabilities-a systematic literature review. IEEE Ac-
cess, 7:109673–109688.
Yalc¸in, M. A., Elmqvist, N., and Bederson, B. B. (2016).
Cognitive stages in visual data exploration. In Pro-
ceedings of the 6th Workshop on Beyond Time and Er-
rors on Novel Evaluation Methods for Visualization,
pages 86–95.
Yigitbasioglu, O. M. and Velcu, O. (2012). A review
of dashboards in performance management: Implica-
tions for design and research. International Journal of
Accounting Information Systems, 13(1):41–59.
Yoo, Y., Lee, H., Jo, I.-H., and Park, Y. (2015). Educa-
tional dashboards for smart learning: Review of case
studies. In Emerging Issues in Smart Learning, pages
145–155. Springer.
Zhang, P. and Soergel, D. (2014). Towards a comprehen-
sive model of the cognitive process and mechanisms
of individual sensemaking. Journal of the Association
for Information Science and Technology, 65(9):1733–
1756.
CSEDU 2023 - 15th International Conference on Computer Supported Education
46