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Transforming learning with meaningful technologies : 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, Delft, the Netherlands, September 16-19, 2019, Proceedings / Maren Scheffel, Julien Broisin, Viktoria Pammer-Schindler, Andri Ioannou, Jan Schneider (eds.).

By: (14th : European Conference on Technology Enhanced Learning (14th : 2019 : Delft, Netherlands)Contributor(s): Scheffel, Maren [editor.] | Broisin, Julien [editor.] | Pammer-Schindler, Viktoria [editor.] | Ioannou, Andri [editor.] | Schneider, Jan (Postdoctoral researcher in educational technologies) [editor.]Material type: TextTextSeries: Serienbezeichnung | Lecture notes in computer science ; 11722. | LNCS sublibrary. SL 3, Information systems and applications, incl. Internet/Web, and HCI.Publisher: Cham, Switzerland : Springer, 2019Description: 1 online resource (xxii, 779 pages) : illustrations (some color)Content type: text Media type: computer Carrier type: online resourceISBN: 9783030297367; 3030297365Other title: EC-TEL 2019Subject(s): Educational technology -- Congresses | Education -- Effect of technological innovations on -- Congresses | Web-based instruction -- Congresses | Education -- Effect of technological innovations on | Educational technology | Web-based instructionGenre/Form: Electronic books. | Conference papers and proceedings. Additional physical formats: No titleDDC classification: 371.33 LOC classification: LB1028.3 | E97 2019ebOnline resources: Click here to access online
Contents:
Intro; Preface; Organization; Contents; Research Papers; Facilitating Students' Digital Competence: Did They Do It?; Abstract; 1 Introduction; 2 Background; 3 Methodology; 4 Findings; 5 Discussion and Conclusions; Acknowledgement; References; Enjoyed or Bored? A Study into Achievement Emotions and the Association with Barriers to Learning in MOOCs; Abstract; 1 Introduction; 2 Theoretical Background and Related Work; 2.1 Barriers to Learning in MOOCs; 2.2 Achievement Emotions; 3 Method; 3.1 Participants; 3.2 Materials; 3.3 Procedures; 3.4 Data Screening; 4 Results; 5 Discussion; 6 Conclusions
AcknowledgementReferences; Identifying Factors for Master Thesis Completion and Non-completion Through Learning Analytics and Machine Learning; Abstract; 1 Introduction; 2 Identified Factors in the Literature Explaining Thesis Completion and Non-completion; 3 Method; 3.1 Sample and Context; 3.2 Data Collection; 3.3 Data Analysis; 4 Results; 4.1 Predicting Completion and Non-completion; 5 Discussion; References; Analyzing Learners' Behavior Beyond the MOOC: An Exploratory Study; 1 Introduction; 2 Related Work; 3 Exploratory Study; 3.1 Context: Tools and Sample
3.2 Data Categorization and Features3.3 Methods; 4 Results; 4.1 Outside the MOOC Behavioral Patterns; 4.2 General and Weekly Grade Prediction; 5 Conclusions and Future Work; References; Building a Learner Model for a Smartphone-Based Clinical Training Intervention in a Low-Income Context: A Pilot Study; Abstract; 1 Background; 1.1 Additive Factor Models (AFMs) and Performance Factor Models (PFMs); 1.2 The Intervention; 2 Methods; 2.1 Study Design, Setting and Participants; 2.2 Study Variables, and Data Management; 2.3 Statistical Methods, Missing Data, and Sensitivity Analyses; 3 Results
4 Discussion4.1 Summary of Findings; 4.2 Relation to Other Studies; 4.3 Implications of Findings; 4.4 Limitations; 5 Conclusions; Acknowledgements; References; Unsupervised Automatic Detection of Learners' Programming Behavior; 1 Introduction; 2 State of the Art; 3 Unsupervised Automatic Detection of Learners' Programming Behavior; 3.1 Application Dataset; 3.2 Phase 1: Identification of Programming Profiles; 3.3 Phase 2: Identification of Students' Behavioral Trajectories; 3.4 Phase 3: Identification of Significant Behavioral Trajectories; 4 Applying the Process with a Real Dataset
4.1 Phase1: Identification of Programming Profiles4.2 Phase 2: Identification of Students' Behavioral Trajectories; 4.3 Phase 3: Identification of Significant Behavioral Trajectories; 4.4 Discussion of the Results; 5 Conclusion and Future Works; References; ``Mirror, mirror on my search ... '': Data-Driven Reflection and Experimentation with Search Behaviour; 1 Introduction; 2 Related Work; 3 A Widget for Reflective Search; 4 Methodology; 4.1 Study 1 -- Experimental Study; 4.2 Study 2 -- Field Study; 5 Results; 5.1 RQ1: Users' Reaction to the Widget; 5.2 RQ2: Reflection; 5.3 RQ3: Search Behaviour
In: Springer eBooksSummary: This book constitutes the proceedings of the 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, held in Delft, The Netherlands, in September 2019. The 41 research papers and 50 demo and poster papers presented in this volume were carefully reviewed and selected from 149 submissions. The contributions reflect the debate around the role of and challenges for cutting-edge 21st century meaningful technologies and advances such as artificial intelligence and robots, augmented reality and ubiquitous computing technologies and at the same time connecting them to different pedagogical approaches, types of learning settings, and application domains that can benefit from such technologies. -- Provided by publisher.
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International conference proceedings.

Includes author index.

Online resource; title from PDF title page (SpringerLink, viewed September 20, 2019).

Intro; Preface; Organization; Contents; Research Papers; Facilitating Students' Digital Competence: Did They Do It?; Abstract; 1 Introduction; 2 Background; 3 Methodology; 4 Findings; 5 Discussion and Conclusions; Acknowledgement; References; Enjoyed or Bored? A Study into Achievement Emotions and the Association with Barriers to Learning in MOOCs; Abstract; 1 Introduction; 2 Theoretical Background and Related Work; 2.1 Barriers to Learning in MOOCs; 2.2 Achievement Emotions; 3 Method; 3.1 Participants; 3.2 Materials; 3.3 Procedures; 3.4 Data Screening; 4 Results; 5 Discussion; 6 Conclusions

AcknowledgementReferences; Identifying Factors for Master Thesis Completion and Non-completion Through Learning Analytics and Machine Learning; Abstract; 1 Introduction; 2 Identified Factors in the Literature Explaining Thesis Completion and Non-completion; 3 Method; 3.1 Sample and Context; 3.2 Data Collection; 3.3 Data Analysis; 4 Results; 4.1 Predicting Completion and Non-completion; 5 Discussion; References; Analyzing Learners' Behavior Beyond the MOOC: An Exploratory Study; 1 Introduction; 2 Related Work; 3 Exploratory Study; 3.1 Context: Tools and Sample

3.2 Data Categorization and Features3.3 Methods; 4 Results; 4.1 Outside the MOOC Behavioral Patterns; 4.2 General and Weekly Grade Prediction; 5 Conclusions and Future Work; References; Building a Learner Model for a Smartphone-Based Clinical Training Intervention in a Low-Income Context: A Pilot Study; Abstract; 1 Background; 1.1 Additive Factor Models (AFMs) and Performance Factor Models (PFMs); 1.2 The Intervention; 2 Methods; 2.1 Study Design, Setting and Participants; 2.2 Study Variables, and Data Management; 2.3 Statistical Methods, Missing Data, and Sensitivity Analyses; 3 Results

4 Discussion4.1 Summary of Findings; 4.2 Relation to Other Studies; 4.3 Implications of Findings; 4.4 Limitations; 5 Conclusions; Acknowledgements; References; Unsupervised Automatic Detection of Learners' Programming Behavior; 1 Introduction; 2 State of the Art; 3 Unsupervised Automatic Detection of Learners' Programming Behavior; 3.1 Application Dataset; 3.2 Phase 1: Identification of Programming Profiles; 3.3 Phase 2: Identification of Students' Behavioral Trajectories; 3.4 Phase 3: Identification of Significant Behavioral Trajectories; 4 Applying the Process with a Real Dataset

4.1 Phase1: Identification of Programming Profiles4.2 Phase 2: Identification of Students' Behavioral Trajectories; 4.3 Phase 3: Identification of Significant Behavioral Trajectories; 4.4 Discussion of the Results; 5 Conclusion and Future Works; References; ``Mirror, mirror on my search ... '': Data-Driven Reflection and Experimentation with Search Behaviour; 1 Introduction; 2 Related Work; 3 A Widget for Reflective Search; 4 Methodology; 4.1 Study 1 -- Experimental Study; 4.2 Study 2 -- Field Study; 5 Results; 5.1 RQ1: Users' Reaction to the Widget; 5.2 RQ2: Reflection; 5.3 RQ3: Search Behaviour

This book constitutes the proceedings of the 14th European Conference on Technology Enhanced Learning, EC-TEL 2019, held in Delft, The Netherlands, in September 2019. The 41 research papers and 50 demo and poster papers presented in this volume were carefully reviewed and selected from 149 submissions. The contributions reflect the debate around the role of and challenges for cutting-edge 21st century meaningful technologies and advances such as artificial intelligence and robots, augmented reality and ubiquitous computing technologies and at the same time connecting them to different pedagogical approaches, types of learning settings, and application domains that can benefit from such technologies. -- Provided by publisher.

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