Schlagwort: hcii

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[publication] Evaluating the Efficacy of Automated Video Editing in Educational Content Production: A Time Efficiency and Learner Perspective Study #tugraz #research

Out publication „Evaluating the Efficacy of Automated Video Editing in Educational Content Production: A Time Efficiency and Learner Perspective Study“ was published.

Abstract:
Automated editing technology offers notable efficiencies in educational video production. This study contrasts the time-saving benefits of automated editing against manual professional editing. Raw learning video footage was recorded in a professional studio with a green screen and presented in a frontal lecture style. The raw footage underwent editing by both an automated tool and professional editors. Time comparison results revealed significant savings with the use of automated tools. The paper further investigates the impact of automated editing on the learning video quality from the learners’ viewpoint. An online survey with 129 participants evaluated their perceptions of potential learning outcomes after viewing automatically and manually edited versions of two videos. The survey found a statistically significant difference in perceived learning potential from one of the videos, although not for both. Additionally, the study considers how differences in study group characteristics might influence these results. In summary, while automated editing presents a compelling case for production time reduction, its impact on the perceived quality of educational videos remains uncertain, necessitating additional research to understand the subtleties of learner interaction with video content.

[article @ publisher’s homepage]
[draft @ ResearchGate]

Reference: Nußbaumer, D., Mair, B., Schön, S., Edelsbrunner, S., Ebner, M. (2024). Evaluating the Efficacy of Automated Video Editing in Educational Content Production: A Time Efficiency and Learner Perspective Study. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2024. Lecture Notes in Computer Science, vol 14722. Springer, Cham. https://doi.org/10.1007/978-3-031-61672-3_15

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[publication] Promotion of Emotional Learning in Technical and Social Domains: A Systematic Review #tugraz #research #hcii

Our publication, „Promotion of Emotional Learning in Technical and Social Domains: A Systematic Review, “ was published.

Abstract:
Different learning approaches and new Learning Environment Systems (LES) are evolving rapidly these days and are designed by taking more and more individual skills and personal characteristics and preferences into account. Also Emotional Learning is gaining more importance when it comes to different learning environments in the technical domain as well as in the social context. Emotional Learning can help to support the overall engagement in learning and approaching learning achievements significantly. This paper should give some deeper insights into Emotional Learning, which possibilities exist to support it in a meaningful way and how feedback of emotional states can be obtained in Learning Environment Systems in higher education. For this purpose a literature review was chosen as the underlying research method to explore and find the necessary answers in various scientific articles, encyclopedias and relevant conference papers from different sources. The outcome will show different state-of-the-art approaches and tools to promote Emotional Learning and how to incorporate emotional learning support in Learning Environments.

[article @ publisher’s homepage]
[draft @ ResearchGate]

Reference: Struger, P., Brünner, B., Ebner, M. (2024). Promotion of Emotional Learning in Technical and Social Domains: A Systematic Review. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2024. Lecture Notes in Computer Science, vol 14723. Springer, Cham. https://doi.org/10.1007/978-3-031-61685-3_18

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[publication] Learning with Videos and Quiz Attempts: Explorative Insights into Behavior and Patterns of MOOC Participants #imoox #video #hcii

Our publication about „Learning with Videos and Quiz Attempts: Explorative Insights into Behavior and Patterns of MOOC Participants“ for the HCII 2023 conference got published:

Abstract:
Many MOOCs use units with videos and quizzes, where a successful attempt after several tries is the basis for a MOOC certificate. A first in-depth analysis of quiz behavior within a MOOC at the Austrian MOOC platform iMooX.at had shown several quiz attempts patterns (Mair et al. 2022). As a next step, the researchers now collected details on video watching within a new edition of the same MOOC and therefore could combine data on quiz and video behavior. This analysis shows similar distribution of the quiz attempt patterns as in our first analysis. Additionally, the analysis indicates that learners who completed more quiz attempts than needed for full point results or passing have a higher average video watching time than learners who only made attempts until reaching a full score or passing.KeywordsMOOC; quiz behaviorVideo behaviorLearningLearning analytics

[full paper @ publisher’s homepage]
[draft @ ResearchGate]

Reference: Mair, B., Schön, S., Ebner, M., Edelsbrunner, S., Leitner, P. (2023). Learning with Videos and Quiz Attempts: Explorative Insights into Behavior and Patterns of MOOC Participants. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2023. Lecture Notes in Computer Science, vol 14040. Springer, Cham. https://doi.org/10.1007/978-3-031-34411-4_22

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[publication] Operationalising Transparency as an Integral Value of Learning Analytics Systems – From Ethical and Data Protection to Technical Design Requirements #gdpr #learninganalytics #tugraz

We did a contribution to the HCII 2023 conference titled „Operationalising Transparency as an Integral Value of Learning Analytics Systems – From Ethical and Data Protection to Technical Design Requirements„. Now you can find the publication online:

Abstract:
With the rising complexity of technology and its introduction into educational settings, the question of trusting and designing trustworthy learning analytics (LA) systems has gained importance. Transparency is one of the values that can contribute to enhancing an LA system’s trustworthiness. It has been included and discussed as a separate core value or principle in many ethical frameworks for LA. Even though these frameworks provide valuable contributions, they are mostly limited to the conceptual level. Defining what transparency entails in the context of LA is an important aspect, nevertheless, the translation and operationalisation of such abstract concepts into technology should be equally considered.In this paper, we focus on the question of how transparency can be translated into concrete design requirements in order to enhance the trustworthiness of LA systems. We present a normative framework in the form of an interdisciplinary Criteria Catalogue for trustworthy LA, which consists of seven core areas, including transparency. Second, we demonstrate how transparency can be translated and operationalised into more specific and low-level elements by using an example of the Learners’ Corner LA dashboard developed within the project “Learning Analytics – Students in Focus”. Third, we share the results of a study conducted to better understand students’ information needs in relation to LA tools and evaluate our design choices for the introduction of three quick information buttons within the Learners’ Corner.

[publication @ book’s homepage]
[draft @ ResearchGate]

Rerference: Veljanova, H., Barreiros, C., Gosch, N., Staudegger, E., Ebner, M., Lindstaedt, S. (2023). Operationalising Transparency as an Integral Value of Learning Analytics Systems – From Ethical and Data Protection to Technical Design Requirements. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2023. Lecture Notes in Computer Science, vol 14040. Springer, Cham. https://doi.org/10.1007/978-3-031-34411-4_37

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[publication] Perceived Effects of Mixed Reality in Distance Learning for the Mining Education Sector #mixedreality #research

One of our contributions to the HCII 2023 was titled „Perceived Effects of Mixed Reality in Distance Learning for the Mining Education Sector“ and it got published right now:

Abstract:
Mixed reality as a tool for teaching has made only limited use of its possibilities so far. However, it brings a plethora of new opportunities, with benefits ranging from interactivity to more vividness. These factors could improve numerous areas of teaching. The mining sector would benefit from new methods combined with mixed reality especially. Therefore, the MiReBooks project was launched: Various applications have been developed that can vividly present content using 3D models, virtual field trips and other methods. To verify and further improve these tools, an evaluation phase was conducted. During two test lectures in distance learning, a total of 23 participants answered a posttest questionnaire. The results showed that the teaching quality could be maintained well by the mixed reality application even in distance learning. Students were satisfied with the methods used, attributed good usability to the tool, and felt integrated into the classroom. At the same time, the team realized that the quality of the lesson depends heavily on the quality of the materials and the expertise of the lecturer. It also became clear that other factors, such as the technical infrastructure and support, are particularly important in this format.

[full article @ publisher’s homepage]
[draft @ ResearchGate]

Reference: Thurner, S., Schön, S., Ebner, M., Leitner, P., Daling, L. (2023). Perceived Effects of Mixed Reality in Distance Learning for the Mining Education Sector. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. HCII 2023. Lecture Notes in Computer Science, vol 14041. Springer, Cham. https://doi.org/10.1007/978-3-031-34550-0_15

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[publication] Development of an Amazon Alexa App for a University Online Search #alexa #research #tugraz

Our chapter about „Development of an Amazon Alexa App for a University Online Search“ for the HCII 2022 conference got published.

Abstract:
Today, our homes become smarter and smarter. We started to interact with our home with Intelligent Personal Assistants, like Amazon Alexa. In this paper we want to present and give a review on the Alexa skill developed for an online search for resources like rooms, courses, and persons. The goal is to provide the users an easy-to-use way to ask for information like phone numbers, e-mail addresses, room details, … and the Alexa Skill should provide this information also in an easy understandable way. We will describe how we solved to formulate suitable search queries from spoken Alexa commands and how we presented them to the user accordingly. Other obstacles like the presentation of the search results, due to the limited context and prioritization for individual search results, to the user will be discussed.

[full article @ book’s homepage]
[draft @ ResearchGate]

Reference: Rupitz, J., Ebner, M., Ebner, M. (2022). Development of an Amazon Alexa App for a University Online Search. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. Designing the Learner and Teacher Experience. HCII 2022. Lecture Notes in Computer Science, vol 13328. Springer, Cham. https://doi.org/10.1007/978-3-031-05657-4_10

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[publication] Evaluation of Mixed Reality Technologies in Remote Teaching #VirtualReality #tugraz #education

Our chapter for the HCII conference 2022 about „Evaluation of Mixed Reality Technologies in Remote Teaching“ got published.

Abstract:
The trend towards remote teaching is steadily increasing and intensified by the current situation of the global pandemic. This is a particular challenge for subjects with a high practical relevance, such as mining engineering education, as practical experiences and on-site excursions are an integral part of the curriculum. In face-to-face teaching settings, mixed reality technologies are already considered a promising medium for the implementation of e.g., virtual field trips. Based on this, the current study addresses the question to what extent the integration of mixed reality technologies is suitable for remote teaching and which strengths and challenges are perceived by students and teachers. For this purpose, two 60-min remote lectures in the field of mining engineering were conducted, in which the use of mixed reality was tested on the basis of shared 360° experiences and 3D models and evaluated by students and teachers. Results reveal that the use of mixed reality in remote teaching was perceived as useful, enabled a realistic experience and improved students’ understanding of presented theory compared to traditional teaching methods. In this paper, we discuss possible potentials and risks of using mixed reality in remote teaching and derive directions for further research.

[full article @ book’s homepage]
[draft @ ResearchGate]

Reference: Daling, L.M., Khoadei, S., Kalkofen, D., Thurner, S., Sieger, J., Shepel, T., Abdelrazeq, A., Ebner, Markus, Ebner, Martin & Isenhardt, I (2022). Evaluation of Mixed Reality Technologies in Remote Teaching. In: Zaphiris, P., Ioannou, A. (eds) Learning and Collaboration Technologies. Novel Technological Environments. HCII 2022. Lecture Notes in Computer Science, vol 13329. Springer, Cham. https://doi.org/10.1007/978-3-031-05675-8_3

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[publication] Towards Trustworthy Learning Analytics Applications: An Interdisciplinary Approach Using the Example of Learning Diaries #LearningAnalytics #tugraz

Our poster/chapter about „Towards Trustworthy Learning Analytics Applications: An Interdisciplinary Approach Using the Example of Learning Diaries“ at HCII 2022 conference is published and available.

Abstract:
Learning analytics (LA) is an emerging field of science due to its great potential to better understand, support and improve the learning and teaching process. Many higher education institutions (HEIs) have already included LA in their digitalisation strategies. This process has been additionally accelerated during the COVID-19 pandemic when HEIs transitioned from face-2-face learning environments to hybrid and e-learning environments and entirely relied on technology to continue operating. Undoubtedly, there was never a time when so much student data was collected, analysed, and reported, which brings numerous ethical and data protection concerns to the forefront. For example, a critical issue when implementing LA is to determine which data should be processed to fulfil pedagogical purposes while making sure that LA is in line with ethical principles and data protection law, such as the European General Data Protection Regulation (GDPR). This article contributes to the discussion on how to design LA applications that are not only useful and innovative but also trustworthy and enable higher education learners to make data-informed decisions about their learning process. For that purpose, we first present the idea and methodology behind the development of our interdisciplinary Criteria Catalogue for trustworthy LA applications intended for students. The Criteria Catalogue is a new normative framework that supports students to assess the trustworthiness of LA applications. It consists of seven defined Core Areas (i.e., autonomy, protection, respect, non-discrimination, responsibility and accountability, transparency, and privacy and good data governance) and corresponding criteria and indicators. Next, we apply this normative framework to learning diaries as a specific LA application. Our goal is to demonstrate how ethical and legal aspects could be translated into specific recommendations and design implications that should accompany the whole lifecycle of LA applications.

[article @ book’s homepage]
[draft @ ResearchGate]

Reference: Veljanova, H., Barreiros, C., Gosch, N., Staudegger, E., Ebner, M., Lindstaedt, S. (2022). Towards Trustworthy Learning Analytics Applications: An Interdisciplinary Approach Using the Example of Learning Diaries. In: Stephanidis, C., Antona, M., Ntoa, S. (eds) HCI International 2022 Posters. HCII 2022. Communications in Computer and Information Science, vol 1582. Springer, Cham. https://doi.org/10.1007/978-3-031-06391-6_19