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1. |
Record Nr. |
UNINA9910476899203321 |
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Autore |
Sander Jennifer |
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Titolo |
Ansätze zur lokalen Bayes'schen Fusion von Informationsbeiträgen heterogener Quellen |
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Pubbl/distr/stampa |
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Karlsruhe, : KIT Scientific Publishing, 2021 |
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ISBN |
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Descrizione fisica |
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1 online resource (342 p.) |
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Collana |
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Karlsruher Schriften zur Anthropomatik |
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Soggetti |
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Maths for computer scientists |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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The solution of various tasks benefits from information fusion or even requires it. The Bayesian fusion methodology is clear, well-founded and fulfills the essential requirements for a meaningful methodology also for fusing the contributions of heterogeneous information sources. In many practically relevant tasks, Bayesian methods cause high, often unacceptable effort. In the work, novel approaches to cope with Bayesian fusion in such situations are formulated and investigated. |
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2. |
Record Nr. |
UNINA9910857784903321 |
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Autore |
Sahin Muhittin |
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Titolo |
Assessment Analytics in Education : Designs, Methods and Solutions / / edited by Muhittin Sahin, Dirk Ifenthaler |
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Pubbl/distr/stampa |
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Cham : , : Springer International Publishing : , : Imprint : Springer, , 2024 |
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ISBN |
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Edizione |
[1st ed. 2024.] |
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Descrizione fisica |
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1 online resource (417 pages) |
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Collana |
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Advances in Analytics for Learning and Teaching, , 2662-2130 |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Educational technology |
Educational tests and measurements |
Digital Education and Educational Technology |
Assessment and Testing |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Nota di contenuto |
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Part 1. Perspectives on Behavior, Engagement, and Interaction -- 1. Foundations of Assessment Analytics (Muhittin Sahin, Dirk Ifenthaler) -- 2. Uncovering Students' Temporal Quiz-Taking Behavior Patterns using Sequence Analysis (Gökhan Akçapınar, Hale Ilgaz, Alper Bayazıt, Denizer Yıldırım) -- 3. Assessment Analytics for Digital Assessments – Identifying Modeling and Interpreting Behavioral Engagement (Okan Bulut, Seyma Nur, Guher Gorgun) -- 4. Guiding Students towards Successful Assessments using Learning Analytics – from Behavioral Data to Formative Feedback (Michael Hanses, Lars van Rijn, Heike Karolyi, Claudia de Witt) -- 5. Transforming Tertiary Education: the Role of Learning Analytics in Improving Students’ Success (Ursina E. Raemy, Stefan J. Troche, Kinga Sipos, Boris Mayer, André Klostermann, Danièle A. Gubler, Natalie Borter) -- 6. Group Cohesion and Performance in Computer-Supported Collaborative Learning (Jan-Bennet Voltmer, Laura Froehlich, Natalia Reich-Stiebert, Jennifer Raimann, Stefan Stürmer) -- Part 2. Perspectives on Analytics, Design, and Indicators -- 7. A Plurality of Measures: from Scale to Modality (Charles Lang, Lalitha Vasudevan, Rhea Jaffer) -- 8. Framework of Assessment Design based on Evidence Centered Design for Assessment Analytics (Cennet Terzi |
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Müftüoğlu, Muhittin Sahin) -- 9. Design of Assessment Task Analytics Dashboard Based on Elo Rating in E-Assessment (Sinan Keskin, Furkan Aydın, Halil Yurdugül) -- 10. Student-Facing Assessment Analytics Dashboards based on Rasch Measurement Theory (Furkan Aydın, Fatma Bayrak, Halil Yurdugül) -- 11. Analysis of Process Data to Advance Computer-Based Assessments in Multilingual Contexts (Martin Hlosta, Jessica M. E. Herzing, Simon Seiler, Sukanya Nath, Florian Keller Zai, Per Bergamin, Andrea B. Erzinger) -- 12. Hierarchical Clustering In Profiling University Students for Online Teaching and Learning (Serhat E. Akhanlı, F. Önay Koçoğlu, Eralp Doğu, Müge Adnan) -- 13. Managing a Large Talent Pool using Assessment Analytics within the Context of the National Internship Program (Salim Atay, Neşe Gülmez, Fatma Bayrak, Yüksel Büşra Çaylak) -- 14. Assessment Analytics: Feedback, Feedup, Feedforward on Bayesian Network (Cennet Terzi Müftüoğlu¬, Ömer Oral, Halil Yurdugül) -- 15. An Architecture for Formative Assessment Analytics of Multimodal Artifacts in E-Portfolios Supported by Artificial Intelligence (Fatima Maya, Karsten D. Wolf) -- 16. Learning Analytics for Assessment and Gamification in Digital Storytelling (Andreea Molnar, Jose Garcia, Patty Kostkova) -- 17. From Clicks to Constructs: an Examination of Validity Evidence of Game-Based Indicators Derived from Theory (Gregory K. W. K. Chung, Tianying Feng) -- 18. Leveraging Online Formative Assessments within the Evolving Landscape of Artificial Intelligence in Education (Caitlin Riegel) -- 19. Towards Fair and Diversity Appropriate E-Assessments (Nikolai Zinke, Sina Lenski, Annabell Brocker, Martin Merkt, Kirsten Gropengießer, Stefan Stürmer, Hannes Schröter) -- 20. Future Directions of Assessment Analytics (Muhittin Sahin, Dirk Ifenthaler). |
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Sommario/riassunto |
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This book is about the current state of research in online assessment. The growth of this field is set to accelerate exponentially with emerging opportunities for automatic data collection and analysis. Yet, the future of online assessment faces major challenges including, perhaps most importantly, the extent to which assessments, when enabled by technology, can serve simultaneously the needs of learners, teachers and those of the enterprise of education. This book details, specifically, the multiple ways in which online assessment can be utilized, such as: Providing virtual coaching or tutoring Offering appropriate scaffolding Allowing analysis of student decision-making Providing the mechanism for students to review and comment on each others digital creations Creating a space for online discussion Providing expert coaching for modeling and animation work With the increased availability of vast and highly varied amounts of data from learners, teachers, learning environments, and administrative systems within educational settings, further opportunities arise for advancing pedagogical assessment practice (Ifenthaler et al., 2018). This book fully details these opportunities, as well as privileges and constraints of analytics-enhanced assessment, harnessing formative as well as summative data from learners and their contexts in order to facilitate learning processes in near real-time and help decisionmakers to improve learning environments. . |
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