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Methodologies and Intelligent Systems for Technology Enhanced Learning, 6th International Conference

Overview of attention for book
Cover of 'Methodologies and Intelligent Systems for Technology Enhanced Learning, 6th International Conference'

Table of Contents

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    Book Overview
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    Chapter 1 Web Technologies and Mobile Tools to Support Sustainable Seamless Learning
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    Chapter 2 An Agent Model of Student’s Affect for Adapting Schooling Strategies
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    Chapter 3 A General Framework for Testing Different Student Team Formation Strategies
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    Chapter 4 Monitoring Level Attention Approach in Learning Activities
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    Chapter 5 Guidelines for Participatory Design of Digital Games in Primary School
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    Chapter 6 BoloTweet: A Micro-Blogging System for Education
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    Chapter 7 Interaction on Distance Education in Virtual Social Networks: A Case Study with Facebook
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    Chapter 8 A “light” Application of Blended Extreme Apprenticeship in Teaching Programming to Students of Mathematics
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    Chapter 9 A Soft Computing Approach to Quality Evaluation of General Chemistry Learning in Higher Education
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    Chapter 10 A Study on Teaching and Learning the von Neumann Machine in a 3D Learning Environment
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    Chapter 11 Identifying Essential Elements in Justifications of Student Drafts
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    Chapter 12 Effectiveness and Usability of TERENCE Adaptive Learning System: The First Pilot Study with Children with Special Educational Needs
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    Chapter 13 The Use of Different Multiple Devices for an Ecological Assessment in Psychological Research: An Experience with a Daily Affect Assessment
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    Chapter 14 Co-Robot Therapy to Foster Social Skills in Special Need Learners: Three Pilot Studies
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    Chapter 15 Towards an Integrated Approach to Diagnosis, Assessment and Treatment in Autism Spectrum Disorders via a Gamified TEL System
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    Chapter 16 Feedbacks in Asynchronous Activities in Virtual Learning Environments: A Case Study
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    Chapter 17 Accuracy of Second Language Skills Self-assessment Through a Web-Based Survey Tool
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    Chapter 18 LTI for Interoperating e-Assessment Tools with LMS
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    Chapter 19 Antecedents of Achievement Emotions: Mixed-Device Assessment with Italian and Australian University Students
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    Chapter 20 Erratum to: Methodologies and Intelligent Systems for Technology Enhanced Learning
Overall attention for this book and its chapters
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (93rd percentile)

Mentioned by

2 news outlets
10 X users


1 Dimensions

Readers on

22 Mendeley
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Methodologies and Intelligent Systems for Technology Enhanced Learning, 6th International Conference
Published by
Advances in Intelligent Systems and Computing, January 2016
DOI 10.1007/978-3-319-40165-2
978-3-31-940164-5, 978-3-31-940165-2

Mauro Caporuscio, Fernando De la Prieta, Tania Di Mascio, Rosella Gennari, Javier Gutiérrez Rodríguez, Pierpaolo Vittorini

X Demographics

X Demographics

The data shown below were collected from the profiles of 10 X users who shared this research output. Click here to find out more about how the information was compiled.
As of 1 July 2024, you may notice a temporary increase in the numbers of X profiles with Unknown location. Click here to learn more.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Spain 1 5%
Finland 1 5%
Unknown 20 91%

Demographic breakdown

Readers by professional status Count As %
Student > Doctoral Student 4 18%
Researcher 3 14%
Student > Master 2 9%
Professor > Associate Professor 2 9%
Other 1 5%
Other 4 18%
Unknown 6 27%
Readers by discipline Count As %
Computer Science 5 23%
Psychology 4 18%
Arts and Humanities 2 9%
Unspecified 2 9%
Social Sciences 1 5%
Other 2 9%
Unknown 6 27%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 23. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 September 2019.
All research outputs
of 25,992,468 outputs
Outputs from Advances in Intelligent Systems and Computing
of 1 outputs
Outputs of similar age
of 402,374 outputs
Outputs of similar age from Advances in Intelligent Systems and Computing
of 1 outputs
Altmetric has tracked 25,992,468 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 93rd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 22.4. This one scored the same or higher as 0 of them.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 402,374 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 93% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them