The evaluation of location-based mobile learning (LBML) concepts and technologies is typically performed using methods known from classical usability engineering, such as questionnaires or interviews. In this paper, we argue that many problems that may occur during LBML become apparent in the learner’s spatio-temporal behavior (i.e., her trajectory). We systematically explore how location tracking and spatial analyses can be used for the evaluation of LBML. Examples with trajectories recorded during a real learning session are presented.
Teachers matter - Challenges of using a location-based mobile learning platformChristian Sailer
Description of the location-based mobile learning platoform
Description og 5 challenges: Environment, technology, learners, teaching, spatio-cognitive competences of teachers
Mobile Learning 2015, Madeira - AN INTEGRATED LEARNING MANAGEMENT SYSTEM FOR ...Christian Sailer
This document discusses an integrated learning management system for location-based mobile learning. It describes how the system allows educators to create location-based learning modules that students can engage with using a mobile app. The system aims to bridge the gap between theoretical classroom learning and hands-on experiences in the field. Requirements for the system include being integrated, interdisciplinary, easy for users, and adaptable to new technologies. Future work may include additional technical capabilities, user interface improvements, and research for a PhD on location-based activities and social learning features.
Gamification of Geoinformation in Swiss Education and ResearchChristian Sailer
The ubiquitous availability of mobile devices at the youth generation affords new concepts of education especially in the field of Geoinformation. Switzerlands' educators and researchers are very active providing new applications for K12 and higher Education. Gamification of such apps is increasing and impacts the GI Education in a positive way.
This presentation was shared at Esri Education Userconference 2015 in San Diego.
- The document summarizes a class on applying GIS methods in public policy decisions that was taught using the open-source software QGIS instead of ESRI's ArcGIS.
- The instructor has a GIS background and helps people with all aspects of the research process. The class was offered through the Frank Batten School of Leadership and Public Policy at the University of Virginia.
- Using QGIS allowed the class to be taught for free on the university's Mac computers since the IT department no longer widely supports desktop software. However, installing QGIS on 17 student systems led to various technical issues to solve.
Vladimir Sahakyan - The National Research and Education Network. Problems and...Arm Igf
The National Research and Education Network of Armenia (ASNET-AM) provides networking solutions and services to academic and research organizations in Armenia. It was created in 1994 and has over 20 years of experience in networking and IT. ASNET-AM operates fiber optic networks and provides services such as cloud storage, email, web hosting, and access to computational facilities. It faces challenges such as unreliable bandwidth and equipment, and aims to address these through server virtualization, alternative network paths, and backup power generators. ASNET-AM collaborates on international projects and provides key infrastructure to support research and education in Armenia.
Scientix 11th SPWatFCL Brussels 18-20 March 2016: Space AwarenessBrussels, Belgium
The Space Awareness project aims to:
1) Stimulate interest in space sciences among students, especially girls and ethnic minorities.
2) Develop educational resources on space topics to foster science learning, global citizenship, and cultural understanding.
3) Create partnerships between individuals from different countries and cultures.
It will provide teaching materials, online courses, and activities centered around space science to help engage over 120,000 students across Europe and beyond.
Teachers matter - Challenges of using a location-based mobile learning platformChristian Sailer
Description of the location-based mobile learning platoform
Description og 5 challenges: Environment, technology, learners, teaching, spatio-cognitive competences of teachers
Mobile Learning 2015, Madeira - AN INTEGRATED LEARNING MANAGEMENT SYSTEM FOR ...Christian Sailer
This document discusses an integrated learning management system for location-based mobile learning. It describes how the system allows educators to create location-based learning modules that students can engage with using a mobile app. The system aims to bridge the gap between theoretical classroom learning and hands-on experiences in the field. Requirements for the system include being integrated, interdisciplinary, easy for users, and adaptable to new technologies. Future work may include additional technical capabilities, user interface improvements, and research for a PhD on location-based activities and social learning features.
Gamification of Geoinformation in Swiss Education and ResearchChristian Sailer
The ubiquitous availability of mobile devices at the youth generation affords new concepts of education especially in the field of Geoinformation. Switzerlands' educators and researchers are very active providing new applications for K12 and higher Education. Gamification of such apps is increasing and impacts the GI Education in a positive way.
This presentation was shared at Esri Education Userconference 2015 in San Diego.
- The document summarizes a class on applying GIS methods in public policy decisions that was taught using the open-source software QGIS instead of ESRI's ArcGIS.
- The instructor has a GIS background and helps people with all aspects of the research process. The class was offered through the Frank Batten School of Leadership and Public Policy at the University of Virginia.
- Using QGIS allowed the class to be taught for free on the university's Mac computers since the IT department no longer widely supports desktop software. However, installing QGIS on 17 student systems led to various technical issues to solve.
Vladimir Sahakyan - The National Research and Education Network. Problems and...Arm Igf
The National Research and Education Network of Armenia (ASNET-AM) provides networking solutions and services to academic and research organizations in Armenia. It was created in 1994 and has over 20 years of experience in networking and IT. ASNET-AM operates fiber optic networks and provides services such as cloud storage, email, web hosting, and access to computational facilities. It faces challenges such as unreliable bandwidth and equipment, and aims to address these through server virtualization, alternative network paths, and backup power generators. ASNET-AM collaborates on international projects and provides key infrastructure to support research and education in Armenia.
Scientix 11th SPWatFCL Brussels 18-20 March 2016: Space AwarenessBrussels, Belgium
The Space Awareness project aims to:
1) Stimulate interest in space sciences among students, especially girls and ethnic minorities.
2) Develop educational resources on space topics to foster science learning, global citizenship, and cultural understanding.
3) Create partnerships between individuals from different countries and cultures.
It will provide teaching materials, online courses, and activities centered around space science to help engage over 120,000 students across Europe and beyond.
2016-05-30 Venia Legendi (CEITER): Maria Jesus Rodriguez Trianaifi8106tlu
This document outlines Venia Lengendi's background and research interests in linking learning design and learning analytics. It discusses trends in education, challenges in technology-enhanced learning, and the vision and goals of the CEITER project to develop an infrastructure that aligns learning design and learning analytics. The proposal involves pedagogical, technological, and methodological approaches, including developing orchestration tools, standards, and conducting iterative design-based research.
A Comparative Study of Indian Learners in Massie Open Online Courses (MOOCs)FutureLearn FLAN
Presented by Janesh Sanzgiri of The Open University at The Open University, Milton Keynes, UK on 15 June 2017. This presentation formed part of the FutureLearn Academic Network section (FLAN Day) of the 38th Computers and Learning Research Group (CALRG) conference. For full details, see http://cloudworks.ac.uk/cloudscape/view/3004
Speakers:
David Lewis, senior analytics consultant, Jisc
Mike Hughes, IT director, City University, London
An opportunity to find out about how an institution has been implementing learning analytics to support the student journey with and opportunity to discuss issues and possibilities that the use of learning analytics may create.
Barriers to Adoption for Learning Analytics at a Dutch UniversityEduworks Network
This document summarizes a presentation about barriers to adopting learning analytics at a Dutch university. It describes the establishment of a focus group on learning analytics and an initial process to define pilot projects. Seven small pilots were organized into three clusters, including using student data to provide feedback and using other data to recommend systems. Organization of the projects presented challenges in clarifying requirements, exploiting synergies, and data ownership. Lessons learned include the need for organizational awareness, documenting failures and agreements, and addressing legal and ethical concerns. A center for data governance and innovation was proposed to help researchers comply with standards.
From assessment to action: Impact of student assessment data on educational policy reform for sustainable future.
Autors: Laura Paviot and Mioko Saito, from IIEP-UNESCO
NTCIR is a series of evaluation workshops designed to enhance research in information access technologies. The NTCIR-12 workshop was held in June 2016 in Tokyo, Japan. The MobileClick-2 task at NTCIR-12 included two subtasks: an iUnit ranking subtask that evaluated systems' ability to predict the importance of information snippets for a given query, and an iUnit summarization subtask to generate a two-layer summary of information snippets and subtopics. The MobileClick-2 task schedule included releasing the test queries in August 2015 and a submission deadline in December 2015.
Data sharing and analytics in research and learningJisc
Learning analytics: progress and solutions - Niall Sclater and Michael Webb, both Jisc
Reading analytics - Clifford Lynch, CNI
Sharing data safely and it's re-use for analytics – David Fergusson, Francis Crick
Jisc and CNI conference, 6 July 2016
20_05_08 «La Red Española de Analítica del Aprendizaje (SNOLA): logros y retos».eMadrid network
The document discusses the Spanish Network of Learning Analytics (SNOLA). It provides an overview of SNOLA's history and achievements, including its growth since 2013 and current research trends among its members. The research trends include predictive analytics, visual analytics, support for active learning strategies, learning design, assessment, and analysis of multimodal/contextual data. Challenges for the field are also discussed.
Measuring and Evaluating Educational Research Literacy in Higher Education: A...Jingjing Lin
This document outlines a plan to host 100 online journal club events in 2023-2024 focused on education sciences. It summarizes a literature review on measuring and evaluating educational research literacy (ERL) in higher education. The review found the most validated instrument for assessing ERL is the LeScEd booklet. Common ERL training formats included courses, but online journal clubs were not frequently used. The document invites researchers to host journal club events through the ResearchIC.com platform to improve ERL training.
Learning analytics in a standardisation contextTore Hoel
This document discusses learning analytics in the context of standardization. It begins by outlining 5 forces that are changing the world: access to data, viewing student data as a resource to be mined and used, concerns about student privacy, and using technology like fitbits and social media monitoring to track students. It then discusses key concepts in learning analytics like definitions, benefits for learners, teachers, and institutions. Other topics covered include the learning analytics process, addressing privacy and data protection, and the potential role of standardization in learning analytics.
This document discusses using data and learning analytics to inform blended learning design and delivery. It describes learning design and curriculum design, as well as learning analytics and how they interact. Potential uses of data discussed include understanding what learning materials and activities students engage with the most, what students are learning, and tailoring learning design based on the characteristics of incoming student cohorts. Challenges around legal/ethical issues, data wrangling, and institutional culture are also addressed. The document encourages discussion of current and potential uses of curriculum analytics within institutions.
Provincial Perspectives on Research Impacts: Eddy Nason, Renata Osika, Krista...CASRAI
When we say “Research Impact” many things come to mind and the reasons for why we are concerned with it vary. The underlying concepts are complex and often require expert knowledge, and there is also no one single interpretation or answer. Stakeholders are diverse and so are the means of communication. Therefore across Canada, we continue to seek more consistent and harmonized ways of telling the “Impact Story.” The panel will reflect on harmonization efforts across provinces.
The document provides an overview of Jisc's Learning Analytics project which aims to help higher education institutions in the UK improve student retention, achievement, and employability through the application of learning analytics techniques. The project involves three core strands: a learning analytics service, toolkit, and community. It also discusses the architecture, data structures, how institutions can get involved, and provides examples of analytics activities at different universities.
Learning Analytics - Vision of the FutureTore Hoel
The document summarizes a presentation about the future of learning analytics given by Tore Hoel. Some key points:
- The presentation discusses the European LACE project, which aims to integrate communities working on learning analytics in schools, workplaces and universities.
- Seven visions of the future of learning analytics in 2025 are presented, including scenarios where analytics are used for educational management, support self-directed learning, or are rarely used due to privacy and data issues.
- The presentation concludes by discussing open systems for learning analytics and international communities focused on this topic.
EMMA Summer School - Rebecca Ferguson - Learning design and learning analytic...EUmoocs
This hands-on workshop will work with learning design tools and with massive open online courses (MOOCs) on the FutureLearn platform to explore how learning design can be used to influence the choice and design of learning analytics. This workshop will be of interest to people who are involved in the design or presentation of online courses, and to those who want to find out more about learning design, learning analytics or MOOCs. Participants will find it helpful to have registered for FutureLearn and explored the platform for a short time in advance of the workshop.
This presentation was given during the EMMA Summer School, that took place in Ischia (Italy) on 4-11 July 2015.
More info on the website: http://project.europeanmoocs.eu/project/get-involved/summer-school/
Follow our MOOCs: http://platform.europeanmoocs.eu/MOOCs
Design and deliver your MOOC with EMMA: http://project.europeanmoocs.eu/project/get-involved/become-an-emma-mooc-provider/
Research in international education can take many forms: whether you are trying to identify best practice in transnational collaboration, investigating strategic planning or measuring outcomes, you face the choice of how best to achieve the desired aims of the study. This session explores some of the mystery surrounding research by looking at some of the practical approaches to undertaking it and by providing insights into the challenges and benefits of the research methods available.
Towards Seamless Mobile Learning with Mixed Reality on Head-Mounted Displays Christian Sailer
Presentation of a co-authored paper with Christian Sailer, David Rudi, Kuno Kurzhals, Martin Raubal (ETH Zurich GIS, Switzerland)
mLearn19 September 16.- 18. 2019, Delft (NL)
Presented at #mlearn19 in Delft, NL
http://iamlearn.org/mlearn/
2016-05-30 Venia Legendi (CEITER): Maria Jesus Rodriguez Trianaifi8106tlu
This document outlines Venia Lengendi's background and research interests in linking learning design and learning analytics. It discusses trends in education, challenges in technology-enhanced learning, and the vision and goals of the CEITER project to develop an infrastructure that aligns learning design and learning analytics. The proposal involves pedagogical, technological, and methodological approaches, including developing orchestration tools, standards, and conducting iterative design-based research.
A Comparative Study of Indian Learners in Massie Open Online Courses (MOOCs)FutureLearn FLAN
Presented by Janesh Sanzgiri of The Open University at The Open University, Milton Keynes, UK on 15 June 2017. This presentation formed part of the FutureLearn Academic Network section (FLAN Day) of the 38th Computers and Learning Research Group (CALRG) conference. For full details, see http://cloudworks.ac.uk/cloudscape/view/3004
Speakers:
David Lewis, senior analytics consultant, Jisc
Mike Hughes, IT director, City University, London
An opportunity to find out about how an institution has been implementing learning analytics to support the student journey with and opportunity to discuss issues and possibilities that the use of learning analytics may create.
Barriers to Adoption for Learning Analytics at a Dutch UniversityEduworks Network
This document summarizes a presentation about barriers to adopting learning analytics at a Dutch university. It describes the establishment of a focus group on learning analytics and an initial process to define pilot projects. Seven small pilots were organized into three clusters, including using student data to provide feedback and using other data to recommend systems. Organization of the projects presented challenges in clarifying requirements, exploiting synergies, and data ownership. Lessons learned include the need for organizational awareness, documenting failures and agreements, and addressing legal and ethical concerns. A center for data governance and innovation was proposed to help researchers comply with standards.
From assessment to action: Impact of student assessment data on educational policy reform for sustainable future.
Autors: Laura Paviot and Mioko Saito, from IIEP-UNESCO
NTCIR is a series of evaluation workshops designed to enhance research in information access technologies. The NTCIR-12 workshop was held in June 2016 in Tokyo, Japan. The MobileClick-2 task at NTCIR-12 included two subtasks: an iUnit ranking subtask that evaluated systems' ability to predict the importance of information snippets for a given query, and an iUnit summarization subtask to generate a two-layer summary of information snippets and subtopics. The MobileClick-2 task schedule included releasing the test queries in August 2015 and a submission deadline in December 2015.
Data sharing and analytics in research and learningJisc
Learning analytics: progress and solutions - Niall Sclater and Michael Webb, both Jisc
Reading analytics - Clifford Lynch, CNI
Sharing data safely and it's re-use for analytics – David Fergusson, Francis Crick
Jisc and CNI conference, 6 July 2016
20_05_08 «La Red Española de Analítica del Aprendizaje (SNOLA): logros y retos».eMadrid network
The document discusses the Spanish Network of Learning Analytics (SNOLA). It provides an overview of SNOLA's history and achievements, including its growth since 2013 and current research trends among its members. The research trends include predictive analytics, visual analytics, support for active learning strategies, learning design, assessment, and analysis of multimodal/contextual data. Challenges for the field are also discussed.
Measuring and Evaluating Educational Research Literacy in Higher Education: A...Jingjing Lin
This document outlines a plan to host 100 online journal club events in 2023-2024 focused on education sciences. It summarizes a literature review on measuring and evaluating educational research literacy (ERL) in higher education. The review found the most validated instrument for assessing ERL is the LeScEd booklet. Common ERL training formats included courses, but online journal clubs were not frequently used. The document invites researchers to host journal club events through the ResearchIC.com platform to improve ERL training.
Learning analytics in a standardisation contextTore Hoel
This document discusses learning analytics in the context of standardization. It begins by outlining 5 forces that are changing the world: access to data, viewing student data as a resource to be mined and used, concerns about student privacy, and using technology like fitbits and social media monitoring to track students. It then discusses key concepts in learning analytics like definitions, benefits for learners, teachers, and institutions. Other topics covered include the learning analytics process, addressing privacy and data protection, and the potential role of standardization in learning analytics.
This document discusses using data and learning analytics to inform blended learning design and delivery. It describes learning design and curriculum design, as well as learning analytics and how they interact. Potential uses of data discussed include understanding what learning materials and activities students engage with the most, what students are learning, and tailoring learning design based on the characteristics of incoming student cohorts. Challenges around legal/ethical issues, data wrangling, and institutional culture are also addressed. The document encourages discussion of current and potential uses of curriculum analytics within institutions.
Provincial Perspectives on Research Impacts: Eddy Nason, Renata Osika, Krista...CASRAI
When we say “Research Impact” many things come to mind and the reasons for why we are concerned with it vary. The underlying concepts are complex and often require expert knowledge, and there is also no one single interpretation or answer. Stakeholders are diverse and so are the means of communication. Therefore across Canada, we continue to seek more consistent and harmonized ways of telling the “Impact Story.” The panel will reflect on harmonization efforts across provinces.
The document provides an overview of Jisc's Learning Analytics project which aims to help higher education institutions in the UK improve student retention, achievement, and employability through the application of learning analytics techniques. The project involves three core strands: a learning analytics service, toolkit, and community. It also discusses the architecture, data structures, how institutions can get involved, and provides examples of analytics activities at different universities.
Learning Analytics - Vision of the FutureTore Hoel
The document summarizes a presentation about the future of learning analytics given by Tore Hoel. Some key points:
- The presentation discusses the European LACE project, which aims to integrate communities working on learning analytics in schools, workplaces and universities.
- Seven visions of the future of learning analytics in 2025 are presented, including scenarios where analytics are used for educational management, support self-directed learning, or are rarely used due to privacy and data issues.
- The presentation concludes by discussing open systems for learning analytics and international communities focused on this topic.
EMMA Summer School - Rebecca Ferguson - Learning design and learning analytic...EUmoocs
This hands-on workshop will work with learning design tools and with massive open online courses (MOOCs) on the FutureLearn platform to explore how learning design can be used to influence the choice and design of learning analytics. This workshop will be of interest to people who are involved in the design or presentation of online courses, and to those who want to find out more about learning design, learning analytics or MOOCs. Participants will find it helpful to have registered for FutureLearn and explored the platform for a short time in advance of the workshop.
This presentation was given during the EMMA Summer School, that took place in Ischia (Italy) on 4-11 July 2015.
More info on the website: http://project.europeanmoocs.eu/project/get-involved/summer-school/
Follow our MOOCs: http://platform.europeanmoocs.eu/MOOCs
Design and deliver your MOOC with EMMA: http://project.europeanmoocs.eu/project/get-involved/become-an-emma-mooc-provider/
Research in international education can take many forms: whether you are trying to identify best practice in transnational collaboration, investigating strategic planning or measuring outcomes, you face the choice of how best to achieve the desired aims of the study. This session explores some of the mystery surrounding research by looking at some of the practical approaches to undertaking it and by providing insights into the challenges and benefits of the research methods available.
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Presentation of a co-authored paper with Christian Sailer, David Rudi, Kuno Kurzhals, Martin Raubal (ETH Zurich GIS, Switzerland)
mLearn19 September 16.- 18. 2019, Delft (NL)
Presented at #mlearn19 in Delft, NL
http://iamlearn.org/mlearn/
ETH GIS and Geoinformation Lab 2018: Discovering Mixed Reality (final present...Christian Sailer
ETH lecture about mobile Geoinformation Technologies
http://gis-lab.ethz.ch/
The purpose of this lab is using cutting-edge technologies to make geoinformation fun, interesting and intuitive.
The document discusses location-based mobile learning using mobile devices and apps. It describes using mobile learning for field trips and outdoor education activities. Students can explore locations, collect data, measure things and analyze their findings. The learning is situated in real world contexts and supports collaboration, peer learning, and assessment. Students may be given missions or tasks to complete at different locations, and their progress and paths can be tracked over time and space. The document provides an example case study of a mobile learning activity at an historic garden site.
This one-page document discusses Generation Mobile and GEOSchoolDay 2017. It mentions Christian Sailer and provides the website geoschoolday.ch, suggesting it relates to an event on that date focused on mobile technology and education.
GPS in Sports by Reto Wick and Christian Sailer / Esri Schweiz AGChristian Sailer
Geobeer.ch #4 at Esri Zürich
Motto "Bewegung im Raum"
"GPS Genauigkeit unter die Lupe genommen" (Reto Wick)
"Potential von Real-Time-Tracking im Sport und für Sportevents" (Christian Sailer
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An evaluation method for location-based mobile learning based on spatio-temporal analysis of learner trajectories
1. ||
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
Chair of Geoinformation Engineering
ETH Zürich (Switzerland)
An evaluation method for location-based mobile
learning based on spatio-temporal analysis of learner
trajectories
2. ||
Learning management system
for location-based mobile
learning
An evaluation method
26.08.2015 2
Scope
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
5. || 26.08.2015 5
Geocaching - Mobile location-based Gaming
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
6. || 26.08.2015 6
Location-based Education
Situatedlearning(Brownetal.1989,Lave&Wenger1991)
Open Classroom
Field work: Explore, Collect, Analyse
Contextuallearning(Pattenetal.2006)
CollaborativeSystem(Tanetal.2010)
Collaboration
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
8. || 26.08.2015 8
OMLETH: A Platform for Location-Based Mobile
Learning at ETH
www.omleth.ch
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
13. ||
Movement
Data
Movement
data is a
temporal
sequence of
position
records:
{id,} x,y,t
26.08.2015 13
Evaluation of learner’s movements (spatio-
temporal trajectories)
x,y,t
x,y,t
x,y,t
x,y,t x,y,t
x,y,t
x,y,t
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x,y,t
x,y,t
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x,y,t
x,y,t
x,y,t
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x,y,t
x,y,t
x,y,t
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x,y,t
x,y,t
x,y,t
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x,y,t
x,y,t
x,y,t
x,y,t
x,y,tx,y,t
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x,y,t
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x,y,tx,y,t
x,y,t
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
14. ||
Single Learner
Multiple unrelated learners
Multiple related learners
26.08.2015 14
Types of evaluation methods
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
15. || 26.08.2015 15
Visual Analytics (VA)
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
16. ||
Seamless spatio-temporal
trajectory
Function linked spatio-temporal
trajectory «Request unit»
26.08.2015 16
Visual Analytics of a single learner
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
19. ||
Seamless spatio-temporal
trajectory
Function linked spatio-temporal
trajectory «Request unit»
26.08.2015 19
Visual Analytics of the learner group (related)
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
23. || 26.08.2015 23
VA – Group Learners related
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
24. || 26.08.2015 24
VA – Group Learners related
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
25. || 26.08.2015 25
VA – Single Learner trajectory – id1
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
26. || 26.08.2015 26
VA – Single Learner trajectory – id7
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
27. || 26.08.2015 27
VA – Single Learner trajectory – id10
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
28. || 26.08.2015 28
VA – Single Learner trajectory – id15
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
29. ||
capturing and analysing learning in context and across
contexts
measuring mobile learning processes and outcomes
respecting learner/participant privacy
assessing mobile technology utility and usability
considering the wider organisational and socio-cultural
context of learning
assessing (in)formality.
26.08.2015 29
Challenges of evaluating mobile learning
Vavuola & Sharples, 2009
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
30. ||
Location accuracy (Geo-) Privacy
26.08.2015 30
Challenges related to our work
Big data
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
32. ||
Empirical studies across disciplines
and demography as well as social
and cultural origin
More GIS components for LMS
26.08.2015 32
Future Work
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
34. ||
Evaluation experiences of mobile learning
Combination of classical evaluation
approaches (interviewing, online forms,
etc.) and our method
Measuring the learning effects /
performance derived from the spatio-
temporal trajectories
26.08.2015 34
My Interests
www.omleth.ch
csailer80
Christian Sailer, Peter Kiefer, Joram Schito and Martin Raubal
Editor's Notes
This work-in-progress paper systematically explores the opportunities of analysing learners’ trajectories for the evaluation of LBML concepts and platforms.
So where I come from? Switzerland, the isle in the european union which fights extremely against the membership to ist neighboorhood!
Of course, obviously many people thnk about chocolat, cows, or our red McGyver Swiss army knive…
.. Or more in context of Geography..
Our Swiss Montains with the famous Matterhorn… which you probably already have seen once when you were hiking?
So, Switzerladn is nice to getting know ……….
My classroom the last ten years: Esri summercamp. Research camp of one week where student learn with GPS and GIS Technology about the ambient of the biggest nationalpark in the Alps. A week of ambitios work and fun.
CLOUGH, G. 2010. Geolearners: Location-based informal learning with mobile and social technologies. Learning
Technologies, IEEE Transactions on, 3, 33-44.
So how do you create your outdoor lecture as teacher?
You all know to famous group of LMS.
The 3 advantagous of LMS are:
You have to register as teacher as well as learner.
Teacher can prepare online learning materials and the LMS provides tools to track and report and evaluate the learning.
But: What about components of learning materials that refer to location?
This project targets the development and evaluation of a platform for location-based mobile learning. It aims at closing the gap between the theoretical study of place-related teaching content, and students’ direct experiences at the respective location. As an add-on to existing didactical concepts, the platform allows to create location-based learning modules, which can later be used in a mobile app.
The requirements were:
Integrated platform for lecturers and students
Interdisciplinary conception
Low technical barriers for usage
Long-term maintainability and adaptability to new technologies
But how about evaluation?
movements of a
single object
Analysis of the object’s behaviour: significant places, times and durations of the visits to different places, typical trips, times and durations of the trips, deviations and their reasons
movements of
multiple unrelated
objects
1) Studies of space use, accessibility, permeability, connectivity, major flows, typical routes between places.
2) Studies of emerging patterns of collective movement:
concentration/ dispersion, convergence/divergence,
propagation of movement characteristics etc.
movements of
multiple related
objects
Studies of relative movements (approaching, encountering, following, evading, etc.) and interactions between the objects.
Logged data consists of:
speed, acceleration, curviness, curvature, sinuosity,
These can be indicators for the reasons why decisions were made. Obviously, the higher the recording rate, the more valid conclusions can be drawn.
acceleration or deceleration could provide evidence of the learner’s uncertainty, time pressure, or (missing) motivation.
zig-zag” path which could mean that the learner had problems finding the target or understanding the map
certain means of transportation. In that case, a spatial analysis can reveal deviations from that path, or transportation mode respectively, for which several reasons may exist: wayfinding problems (see above), changes in the environment (e.g., a construction site or flooded area), unclear communication on the path to take, or physical activity avoidance behavior. For identifying the reason additional sources need to be used (including simply asking the student).
Learning can also occur within a team that pursuits the same target. Several studies have shown that the motivation rises when working with peers [21]. Knowledge can be exchanged and the constructivist learning rises as well on the condition that interaction by discussion between the learners is frequent. Each group member contributes to the team’s success by occupying a specific role. However, social competence plays an important part. Consequently, the movement patterns differ between the roles occupied.
The trendsetter motion pattern was introduced by [17] as one trend-setting moving point object that anticipates the motion of n others with the REMO approach.
Once a trendsetter has been detected as leader, the other group members act as followers. Followers can indeed be interested in the LBML process and consequently like to adapt the leader’s behavior. However, other followers prefer to evade the responsibility of contributing to the group’s success. One assumption can be that interested or engaged learners are always sited close to the leader, moving at the same speed along the route. In contrast, uninterested people are located more distant to the group leader. Consequently, the speed pattern may provide evidence for distinguishing between interested and uninterested learners. Repeating outdoor learning units with the same group of learners could support these indications
Learning can also occur within a team that pursuits the same target. Several studies have shown that the motivation rises when working with peers [21]. Knowledge can be exchanged and the constructivist learning rises as well on the condition that interaction by discussion between the learners is frequent. Each group member contributes to the team’s success by occupying a specific role. However, social competence plays an important part. Consequently, the movement patterns differ between the roles occupied.
The trendsetter motion pattern was introduced by [17] as one trend-setting moving point object that anticipates the motion of n others with the REMO approach.
Once a trendsetter has been detected as leader, the other group members act as followers. Followers can indeed be interested in the LBML process and consequently like to adapt the leader’s behavior. However, other followers prefer to evade the responsibility of contributing to the group’s success. One assumption can be that interested or engaged learners are always sited close to the leader, moving at the same speed along the route. In contrast, uninterested people are located more distant to the group leader. Consequently, the speed pattern may provide evidence for distinguishing between interested and uninterested learners. Repeating outdoor learning units with the same group of learners could support these indications
Summarized in the geofence
Summarized in the geofence
Summarized in the geofence
Summarized in the geofence
Vavuola and Sharples proposed six challenges in evaluating mobile learning [6]:
Capturing and analysing learning in context and across contexts: location is recognized as one of the most important – if not the most important form of context. By tracking location during learning, we enable the analysis of learning behavior, strategies and success in relation to specific locations, as well as across locations.
Measuring mobile learning processes and outcomes: learning processes in LBML almost always include locomotion. Perceiving, reasoning about, and understanding environmental phenomena happens at locations, as well as during locomotion between locations. A learner’s trajectory thus reflects the progress and individual development of the learning process.
Respecting learner/participant privacy: as discussed in the section Privacy, LBML is not more privacy-breaching than other eLMS. However, regulatory approaches to privacy need to be respected by LBML platforms which are summarized by the five principles of fair information practices in [27]. They point out that various types of inferences of movement patterns make anonymity and pseudonymity much harder to maintain than in other privacy applications, such as the Internet. Because information about personal location is highly dynamic, the potential uses and privacy implications of dynamic location information change over time. Finally they caution that without proper protection, the location information generated by location-aware systems could conceivably be abused or unfairly used in almost any domain of human, social, or economic activity.
Assessing mobile technology utility and usability: trajectory analyses can show whether learners get lost, thus revealing problems with the navigation assistance of the system (e.g., the map design). Also, systematic positioning errors become apparent in the trajectories, such as urban canyons shadowing the GPS signal in certain areas, which means a different type of positioning technology could become necessary for that specific region.
Considering the wider organizational and socio-cultural context of learning: the social context of learning could be detected if an analysis of movement dynamics within a learning group can be performed. We also mentioned that correlations between the socio-cultural context and typical movement patterns can be detected through cluster analyses based on large collections of trajectory data.
Assessing (in)formality: learning in LBML can take place at any time, independent from a formal classroom setting. This informal setting could lead to students not visiting the places they are supposed to. As explained in the section Movement of single learners, such deviations from a pre-defined path can be detected in trajectories.
Location accuracy
Before evaluate or interpret such observations it is required that the location accuracy is always known and taken into account.
Big data
Storage, Web rendering, Benefit
GeoPrivacy
In the case of LBML platforms, privacy issues are, first of all, the same issues as for (non location-based, non-mobile) e-learning [23]. For instance, when solving tasks in an e-learning management system (eLMS) over the web, the learner needs to trust all parties who get access to her data, which includes at least the eLMS provider and the teacher. It is plausible to simply assume a trustful teacher-student relationship, since otherwise learning would be seriously hampered. For the eLMS provider (in our case: the LBML management system provider) we suggest to choose a trustworthy party, such as the educational institution.
With data mining techniques it is possible to identify real persons based on their trajectory, even if the user is anonymized with a pseudonym [25] based on the detection of frequently visited locations (home, work, etc.) and profiles created from other data sources. The movement behavior shown during LBML, however, is usually not related to the daily routines or interests of the individual, but determined either by the pre-defined path, or by the set of locations available in the area of the learning unit. In other words, deanonymization will be difficult because all learners visit (more or less) the same set of locations.
Nextgen GI Education supports 21st century skills with Critical Thinking, Creative Thinking, Collaborating, Communicating. Nextgen geography is learner-centred and mobile technolog-based.
The seamless-gaming approach shoul be adapated on learning. ->Serious gaming
Education is more outside the school, location-based. With LMS teachers can control also spatially.
And that Education is more LBS, Geography will profit with ist knowldge about spatial concepts
Therefore Mobile Programming in Geography Education is essentially to generate such mobile apps and analytics to
keep the lead of GIS!!
21st Century Skills: Critical thinking, process analytics, spatial analytics
Learner-centred: Exploring, Surveying, Sensoring
Mobile First: Anywhere, anytime, ubiquitios
Learning like Gaming: Collaborative, informal, constructiviste, creative and seamless
Location-based Education: Location-based mobile Games, Mobile Learning / In situ Learning / Geographical Learning
Development: Process (Python) and App (HTML5, JS CSS3) Development, Android (Java)
Learning Skills
Critical Thinking
Creative Thinking
Collaborating
Communicating
Literacy Skills
Information Literacy
Media Literacy
Technology Literacy
Life Skills
Flexibility
Initiative
Social Skills
Productivity
Leadership
We will address peers across disciplines and demography as well as social and cultural origin to generate profound knowledge about LBML.
Although our method enables new types of evaluations for LBML, it is clear that the method needs to be combined with classical evaluation approaches,