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Viberg, O., Mutimukwe, C., Hrastinski, S., Cerratto‐Pargman, T. & Lilliesköld, J. (2024). Exploring teachers' (future) digital assessment practices in higher education: Instrument and model development. British Journal of Educational Technology
Open this publication in new window or tab >>Exploring teachers' (future) digital assessment practices in higher education: Instrument and model development
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2024 (English)In: British Journal of Educational Technology, ISSN 0007-1013, E-ISSN 1467-8535Article in journal (Refereed) Published
Abstract [en]

Digital technologies are increasingly used in assessment. On the one hand, this use offers opportunities for teachers to practice assessment more effectively, and on the other hand, it brings challenges to the design of pedagogically sound and responsible digital assessment. There is a lack of validated instruments and models that explain, assess and support teachers' critical pedagogical practice of digital assessment. This explorative work first develops and validates a survey instrument to examine teachers' digital assessment practices. Secondly, we build a model to investigate to what extent teachers' pedagogical digital assessment knowledge is a foundation for the future of digital assessment (ie, authentic, accessible, automated, continuous and responsible). A total of 219 university teachers at a large European university participated in the survey study. Factor exploratory analysis and structural equation modelling were used to validate the reliability and validity of items and internal causal relations of factors. The results show the survey is a valid and reliable instrument for assessing teachers' digital assessment practice in higher education. Teachers' pedagogical knowledge and pedagogical content knowledge of digital assessment is critical, while teachers' technological pedagogical knowledge seems to have a more limited impact on the future of digital assessment. 

Place, publisher, year, edition, pages
Wiley, 2024
National Category
Pedagogy
Identifiers
urn:nbn:se:kth:diva-346257 (URN)10.1111/bjet.13462 (DOI)2-s2.0-85189638407 (Scopus ID)
Note

QC 20240514

Available from: 2024-05-09 Created: 2024-05-09 Last updated: 2024-05-14Bibliographically approved
Iop, A., Viberg, O., Francis, K., Norström, V., Mattias Persson, D., Wallin, L., . . . Matviienko, A. (2024). Exploring the Influence of Object Shapes and Colors on Depth Perception in Virtual Reality for Minimally Invasive Neurosurgical Training. In: CHI 2024 - Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Sytems: . Paper presented at 2024 CHI Conference on Human Factors in Computing Sytems, CHI EA 2024, Hybrid, Honolulu, United States of America, May 11 2024 - May 16 2024. Association for Computing Machinery, Article ID 154.
Open this publication in new window or tab >>Exploring the Influence of Object Shapes and Colors on Depth Perception in Virtual Reality for Minimally Invasive Neurosurgical Training
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2024 (English)In: CHI 2024 - Extended Abstracts of the 2024 CHI Conference on Human Factors in Computing Sytems, Association for Computing Machinery , 2024, article id 154Conference paper, Published paper (Refereed)
Abstract [en]

Minimally invasive neurosurgery (MIS) involves inserting a medical instrument, e.g., a catheter, through a small incision to target an area inside the patient's body. Training surgeons to perform MIS is challenging since the surgical site is not directly visible from their perspective. In this paper, we conducted two pilot studies focused on object shapes and colors to collect preliminary results on their influence on depth perception for MIS in Virtual Reality. In the first study (N = 8), participants inserted a virtual catheter into objects of different shapes. In the second study (N = 5), they observed the insertion of a virtual catheter into objects of different colors and backgrounds under different lighting conditions. We found that participants' precision decreased with distance and was lower with the skull shape than with a cube. Moreover, depth perception was higher with blue backgrounds under better lighting conditions.

Place, publisher, year, edition, pages
Association for Computing Machinery, 2024
Keywords
depth perception, minimally invasive neurosurgery, virtual reality
National Category
Neurology
Identifiers
urn:nbn:se:kth:diva-347323 (URN)10.1145/3613905.3650813 (DOI)2-s2.0-85194135109 (Scopus ID)
Conference
2024 CHI Conference on Human Factors in Computing Sytems, CHI EA 2024, Hybrid, Honolulu, United States of America, May 11 2024 - May 16 2024
Note

QC 20240613

Part of ISBN 979-840070331-7

Available from: 2024-06-10 Created: 2024-06-10 Last updated: 2024-06-13Bibliographically approved
Dunder, N., Lundborg, S., Wong, J. & Viberg, O. (2024). Kattis vs ChatGPT: Assessment and Evaluation of Programming Tasks in the Age of Artificial Intelligence. In: LAK 2024 Conference Proceedings - 14th International Conference on Learning Analytics and Knowledge: . Paper presented at 14th International Conference on Learning Analytics and Knowledge, LAK 2024, Kyoto, Japan, Mar 18 2024 - Mar 22 2024 (pp. 821-827). Association for Computing Machinery (ACM)
Open this publication in new window or tab >>Kattis vs ChatGPT: Assessment and Evaluation of Programming Tasks in the Age of Artificial Intelligence
2024 (English)In: LAK 2024 Conference Proceedings - 14th International Conference on Learning Analytics and Knowledge, Association for Computing Machinery (ACM) , 2024, p. 821-827Conference paper, Published paper (Refereed)
Abstract [en]

AI-powered education technologies can support students and teachers in computer science education. However, with the recent developments in generative AI, and especially the increasingly emerging popularity of ChatGPT, the effectiveness of using large language models for solving programming tasks has been underexplored. The present study examines ChatGPT's ability to generate code solutions at different difficulty levels for introductory programming courses. We conducted an experiment where ChatGPT was tested on 127 randomly selected programming problems provided by Kattis, an automatic software grading tool for computer science programs, often used in higher education. The results showed that ChatGPT independently could solve 19 out of 127 programming tasks generated and assessed by Kattis. Further, ChatGPT was found to be able to generate accurate code solutions for simple problems but encountered difficulties with more complex programming tasks. The results contribute to the ongoing debate on the utility of AI-powered tools in programming education.

Place, publisher, year, edition, pages
Association for Computing Machinery (ACM), 2024
Keywords
Academic Integrity, Automated Grading, ChatGPT, Programming Education
National Category
Educational Sciences
Identifiers
urn:nbn:se:kth:diva-344554 (URN)10.1145/3636555.3636882 (DOI)2-s2.0-85187550433 (Scopus ID)
Conference
14th International Conference on Learning Analytics and Knowledge, LAK 2024, Kyoto, Japan, Mar 18 2024 - Mar 22 2024
Note

QC 20240321

 Part of ISBN 9798400716188

Available from: 2024-03-20 Created: 2024-03-20 Last updated: 2024-03-21Bibliographically approved
Buvari, S., Viberg, O., Iop, A. & Romero, M. (2023). A student-centered learning analytics dashboard towards course goal achievement in STEM education. In: Responsive and Sustainable Educational Futures: 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Proceedings. Paper presented at Proceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023, Aveiro, Portugal, Sep 4 2023 - Sep 8 2023 (pp. 698-704). Springer Nature
Open this publication in new window or tab >>A student-centered learning analytics dashboard towards course goal achievement in STEM education
2023 (English)In: Responsive and Sustainable Educational Futures: 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Proceedings, Springer Nature , 2023, p. 698-704Conference paper, Published paper (Refereed)
Abstract [en]

Online learning has become an everyday form of learning for many students across different disciplines, including STEM subjects in the setting of higher education. Studying in these settings requires students to self-regulate their learning to a higher degree as compared to campus-based education. A vital aspect of self-regulated learning is the application of goal-setting strategies. Universities act to support students’ goal-setting through the achievement of course learning outcomes, which work both as a promise and metric of academic achievement. However, a lack of clear integration between course activities and course learning outcomes leaves a dissonance between students’ study efforts and the course progress. This demo study presents a student-centered learning analytics dashboard aimed at assisting students in their achievement of course learning goals in the setting of STEM higher education. The dashboard was designed using a design science methodological approach. Thirty-seven students have contributed to its development and evaluation during different stages of the design process, including the conceptual iterative design and prototyping. The preliminary results show that students found the tool to be easy to use and useful for the achievement of the course goals.

Place, publisher, year, edition, pages
Springer Nature, 2023
Keywords
Learning Analytics Dashboard, Learning Outcomes, Participatory Design, STEM Higher Education
National Category
Didactics Learning Human Computer Interaction
Identifiers
urn:nbn:se:kth:diva-337821 (URN)10.1007/978-3-031-42682-7_64 (DOI)2-s2.0-85171977964 (Scopus ID)
Conference
Proceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023, Aveiro, Portugal, Sep 4 2023 - Sep 8 2023
Note

Part of ISBN 9783031426810

QC 20231009

Available from: 2023-10-09 Created: 2023-10-09 Last updated: 2023-10-12Bibliographically approved
Viberg, O., Kukulska-Hulme, A. & Peeters, W. (2023). Affective Support for Self-Regulation in Mobile-Assisted Language Learning. International Journal of Mobile and Blended Learning, 15(2)
Open this publication in new window or tab >>Affective Support for Self-Regulation in Mobile-Assisted Language Learning
2023 (English)In: International Journal of Mobile and Blended Learning, ISSN 1941-8647, E-ISSN 1941-8655, Vol. 15, no 2Article in journal (Refereed) Published
Abstract [en]

Mobile-assisted language learning (MALL) research includes examination and development of second language learners' cognitive and metacognitive self-regulated learning skills, but the affective learning component of self-regulation in this context remains largely unexplored. Support for affective learning, which is defined by learners' beliefs, attitudes, and emotions, has been shown to influence learners' cognitive processes, performance, and engagement considerably, and is therefore critical to promote and foster throughout the learning process. This paper defines the importance of supporting affect in MALL, sets out a theoretical perspective on supporting affective self-regulation in MALL, and elaborates on what designers and teachers can do to facilitate affective development through the use of mobile technology, learning analytics, and artificial intelligence. It examines and further delineates the role of affective computing and the role of the teacher in fully harnessing the affective affordances of MALL.

Place, publisher, year, edition, pages
IGI Global, 2023
Keywords
Affect Artificial Intelligence Learner Autonomy Learning Analytics L2 Learning Mobile App Design Mobile-Assisted Language Learning Self-Regulated Learning Support
National Category
Information Systems
Identifiers
urn:nbn:se:kth:diva-325214 (URN)10.4018/IJMBL.318226 (DOI)000942685800004 ()2-s2.0-85149184662 (Scopus ID)
Note

QC 20230403

Available from: 2023-04-03 Created: 2023-04-03 Last updated: 2023-04-03Bibliographically approved
Hrastinski, S., Stenbom, S., Saqr, M., Jansson, M. & Viberg, O. (2023). Examining the Development of K-12 Students' Cognitive Presence over Time: The Case of Online Mathematics Tutoring. ONLINE LEARNING, 27(3), 252-270
Open this publication in new window or tab >>Examining the Development of K-12 Students' Cognitive Presence over Time: The Case of Online Mathematics Tutoring
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2023 (English)In: ONLINE LEARNING, ISSN 2472-5749, Vol. 27, no 3, p. 252-270Article in journal (Refereed) Published
Abstract [en]

In this article, we focus on the cognitive presence element of the Community of Inquiry (CoI) framework. Cognitive presence consists of four categories: Triggering Event, Exploration, Integration, and Resolution. These categories have been described as phases following an idealized logical sequence, although the phases should not be seen as immutable. Few studies have empirically examined how the four categories develop over time during the inquiry process. This article uses learning analytics methods to study transitions between the categories in K-12 online mathematics tutoring. It was statistically most probable that the tutoring sessions started with Triggering Event (95%) and then transitioned to Exploration (51%). The transitions from Exploration to Integration (18%) and Integration to Resolution (21%) achieved statistical significance but were less likely. In fact, it was more likely that the tutoring sessions transitioned from Integration to Exploration (39%) and Resolution to Exploration (36%). In conclusion, the findings suggest that the idealized logical sequence is evident in the data but that other transitions occur as well; especially Exploration recurs throughout the sessions. It seems challenging for students to reach the Integration and Resolution categories. As the CoI framework is commonly adopted in practice, it is important that tutors and educators understand that the categories of cognitive presence will often not play out in idealized ways, underlining their role in supporting how the inquiry process unfolds. In order to gain an improved understanding of the inquiry process, future research is suggested to investigate how the presences and categories of the CoI framework develop over time in different educational settings.

Place, publisher, year, edition, pages
The Online Learning Consortium, 2023
Keywords
Cognitive presence, community of inquiry, time, online mathematics tutoring
National Category
Learning Interaction Technologies
Identifiers
urn:nbn:se:kth:diva-339575 (URN)10.24059/olj.v27i3.3481 (DOI)001085999700008 ()2-s2.0-85174800397 (Scopus ID)
Note

QC 20231115

Available from: 2023-11-15 Created: 2023-11-15 Last updated: 2023-11-30Bibliographically approved
Khosravi, H., Viberg, O., Kovanovic, V. & Ferguson, R. (2023). Generative AI and Learning Analytics. Journal of Learning Analytics, 10(3), 1-6
Open this publication in new window or tab >>Generative AI and Learning Analytics
2023 (English)In: Journal of Learning Analytics, E-ISSN 1929-7750, Vol. 10, no 3, p. 1-6Article in journal, Editorial material (Other academic) Published
Abstract [en]

This editorial looks back at the Journal of Learning Analytics (JLA) in 2023 and forward to 2024. Considering the recent proliferation of large language models such as GPT4 and Bard, the first section of this editorial points to the need for robust Generative AI (GenAI) analytics, calling for consideration of how GenAI may impact learning analytics research and practice. The second section looks back over the past year, providing statistics on submissions and considering the cost of publication in an open-access journal.

Place, publisher, year, edition, pages
Society for Learning Analytics Research, 2023
Keywords
GenAI, Generative AI, learning analytics, practice, research
National Category
Learning
Identifiers
urn:nbn:se:kth:diva-342172 (URN)10.18608/jla.2023.8333 (DOI)001133089300002 ()2-s2.0-85180720417 (Scopus ID)
Note

QC 20240115

Available from: 2024-01-15 Created: 2024-01-15 Last updated: 2024-02-29Bibliographically approved
Pargman, T. C., McGrath, C., Viberg, O. & Knight, S. (2023). New Vistas on Responsible Learning Analytics: A Data Feminist Perspective. JOURNAL OF LEARNING ANALYTICS, 10(1), 133-148
Open this publication in new window or tab >>New Vistas on Responsible Learning Analytics: A Data Feminist Perspective
2023 (English)In: JOURNAL OF LEARNING ANALYTICS, ISSN 1929-7750, Vol. 10, no 1, p. 133-148Article in journal (Refereed) Published
Abstract [en]

The focus of ethics in learning analytics (LA) frameworks and guidelines is predominantly on procedural elements of data management and accountability. Another, less represented focus is on the duty to act and LA as a moral practice. Data feminism as a critical theoretical approach to data science practices may offer LA research and practitioners a valuable lens through which to consider LA as a moral practice. This paper examines what data feminism can offer the LA community. It identifies critical questions for further developing and enabling a responsible stance in LA research and practice taking one particular case - algorithmic decision-making - as a point of departure.

Place, publisher, year, edition, pages
Society for Learning Analytics Research, 2023
Keywords
Data feminism, critical theory, ethical guidelines, learning analytics, responsibility
National Category
Computer Sciences Gender Studies
Identifiers
urn:nbn:se:kth:diva-325611 (URN)10.18608/jla.2023.7781 (DOI)000952896000002 ()2-s2.0-85150729861 (Scopus ID)
Note

QC 20230406

Available from: 2023-04-06 Created: 2023-04-06 Last updated: 2023-04-06Bibliographically approved
Iop, A., Viberg, O., Elmi-Terander, A., Edström, E. & Romero, M. (2023). On Extended Reality Objective Performance Metrics for Neurosurgical Training. In: Responsive and Sustainable Educational Futures: 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Proceedings. Paper presented at Proceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023, Aveiro, Portugal, Sep 4 2023 - Sep 8 2023 (pp. 573-579). Springer Nature
Open this publication in new window or tab >>On Extended Reality Objective Performance Metrics for Neurosurgical Training
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2023 (English)In: Responsive and Sustainable Educational Futures: 18th European Conference on Technology Enhanced Learning, EC-TEL 2023, Proceedings, Springer Nature , 2023, p. 573-579Conference paper, Published paper (Refereed)
Abstract [en]

The adoption of Extended Reality (XR) technologies for supporting learning processes is an increasingly popular research topic for a wide variety of domains, including medical education. Currently, within this community, the metrics applied to quantify the potential impact these technologies have on procedural knowledge acquisition are inconsistent. This paper proposes a practical definition of standard metrics for the learning goals in the application of XR to surgical training. Their value in the context of previous research in neurosurgical training is also discussed. Objective metrics of performance include: spatial accuracy and precision, time-to-task completion, number of attempts. The objective definition of what the learner’s aims are enables the creation of comparable XR systems that track progress during training. The first impact is to provide a community-wide metric of progress that allows for consistent measurements. Furthermore, a measurable target opens the possibility for automated performance assessments with constructive feedback.

Place, publisher, year, edition, pages
Springer Nature, 2023
Keywords
Extended Reality, Neurosurgical Education, Performance Metrics, Procedural Knowledge, Surgical Simulation
National Category
Other Computer and Information Science
Identifiers
urn:nbn:se:kth:diva-337819 (URN)10.1007/978-3-031-42682-7_44 (DOI)2-s2.0-85172000439 (Scopus ID)
Conference
Proceedings of the 18th European Conference on Technology Enhanced Learning, ECTEL 2023, Aveiro, Portugal, Sep 4 2023 - Sep 8 2023
Note

Part of ISBN 9783031426810

QC 20231009

Available from: 2023-10-09 Created: 2023-10-09 Last updated: 2023-10-12Bibliographically approved
Viberg, O., Muñoz-Merino, P. J., Papathoma, T., Jivet, I. & Perifanou, M. (2023). Preface. In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics): . Springer Nature, 14200 LNCS
Open this publication in new window or tab >>Preface
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2023 (English)In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Springer Nature , 2023, Vol. 14200 LNCSChapter in book (Other academic)
Place, publisher, year, edition, pages
Springer Nature, 2023
National Category
Computer Sciences
Identifiers
urn:nbn:se:kth:diva-337895 (URN)2-s2.0-85171993531 (Scopus ID)
Note

Part of ISBN 9783031426810

QC 20231016

Available from: 2023-10-16 Created: 2023-10-16 Last updated: 2023-10-16Bibliographically approved
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ORCID iD: ORCID iD iconorcid.org/0000-0002-8543-3774

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