I.Kourousis
I.Kourousis

Ioannis Kourousis is profesor IT and instructional designer.  He has studied Digital Systems and Technology Instruction at the University of Pireaus and he holds a Msc in E-learning from the same institution and a Msc in Direction and School management from the International University of La Rioja.

 

Website URL: http://goo.gl/wDox3H

Attention - deficit / hyperactivity disorder (ADHD)

Published in Glossary

Attention - deficit / hyperactivity disorder (ADHD)


Attention - deficit / hyperactivity disorder (ADHD) is a psychiatric disorder that has neurobiological basis (Michanie, 2004). 

People with ADHD have attention deficit, impulsivity and hyperactivity.  It occurs on a percentage 5-7% of the school population and a ratio of 3 to 1 in favor of boys (Greek National Association of People with Attention Deficit Hyperactivity Disorder).  

It is the current diagnostic label not only for children but also for adults who have significant problems with attention and excessive activity.  Both children and adults with ADHD represent a rather heterogeneous population that displays significant variation in the degree of their symptoms, age of onset, cross-situational pervasiveness of those symptoms, and the extent to which other disorders occur in relation with ADHD (Barkley, 2014).

 

References

  • Barkley, R. A. (Ed.). (2014). Attention-deficit hyperactivity disorder: A handbook for diagnosis and treatment. Guilford Publications.
  • Michanie, C. (2004). Diferencias del trastorno por déficit de atención en el niño y el adulto: consideraciones diagnósticas y terapéuticas. Psicofarmacología Psicodinámica IV-Actualizaciones, 59-82.
  • Greek National Association of People with Attention Deficit Hyperactivity Disorder (DEPY)  http://goo.gl/4R4aGQ
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Cloud computing

Published in Glossary

Cloud computing

Cloud computing, has its roots in late of 2007, but is becoming one of the next IT industry hot topics because it promotes the idea that users can move their data and applications to a remote “Cloud” and then they can have access in a simple and pervasive way.

This means that cloud computing  offers flexible dynamic IT infrastructures and configurable software services (Armbrust et al, 2009).

There are several definitions about Cloud Computing which refer to the applications delivered as services, hardware, software that provide those services. The Cloud is a platform or infrastructure that enables the execution of services or applications following the requirements.

There are main types of clouds: Infrastructure as a Service (IaaS), Platform as a Service (PaaS)  and Software as a Service (SaaS),

 

References

  • Armbrust, M; Fox, A; Griffith, R; Joseph, AD; Katz, RH; Konwinski, A; Lee, G; Patterson, DA; Rabkin, A; Stoica, I &Zaharia, M (2009), ‘Above the Clouds: A Berkeley View of Cloud Computing’. Technical Report No.UCB/EECS-2009-28 – available at http://goo.gl/Pc5G
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Intelligent Tutoring Systems (ITSs)

Published in Glossary

Intelligent Tutoring Systems (ITSs)

In 1982, Sleeman and Brown reviewed Computer Aided Instruction (CAI) systems and identified an advanced type, which was named Intelligent Tutoring Systems (ITS). 

ITSs are computer-based systems and use the functionalities of Artificial Intelligence methods.  Their key element is their potential to provide user-adapted presentation of the teaching material (Vassileva, 1997).

ITSs create models for representing the pedagogical decisions and make inferences about a student’s mastery of topics in order to dynamically adapt the content or style of instruction (Wenger 1987).  It is argued that few ITS techniques are curriculum sequencing technology, intelligent solution analyses and problem solving support (Brusilovsky and Peylo, 2003).

 

References

  • Brusilovsky, P., and Peylo, C. (2003). Adaptive and Intelligent Web Based Educational Systems.International Journal of Artificial Intelligence in Education Vol. 13, 156-169.
  • D.H. Sleeman& J.S. Brown (1982). Intelligent Tutoring Systems: an overview. In Intelligent Tutoring Systems, eds D. Sleeman& J.S. Brown, Academic: London, pp1-11.
  • Vassileva, J.: Dynamic Courseware Generation. Journal of Computing and Information Technology 5 (1997) 87-102.
  • Wenger, E. (1987). Artificial Intelligence and Tutoring Systems. Los Altos, CA: MorganKaufmann.
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Learning analytics

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Learning analytics

The evolution of Learning Analytics (LA) is based on the fast-growing area Technology-Enhanced Learning (TEL) research.  The major drivers of LA are the Big Data ("datasets whose size is beyond the ability of typical database software tools to capture, store, manage and analyse"), the online learning and the increasing political/economical demand for measuring, interpreting and improving performance of educational institutions.  The field of LA originates from the disciplines of Educational Data Mining (EDM), Academic Analytics, Web Analytics, Social Network Analysis or Business Intelligence (BI) (Ferguson, 2012).

A first definition of LA "is the use of intelligent data, learner-produced data, and analysis models to discover information and social connections, and to predict and advise on learning (Siemens, 2010).  The emergence of LA as a field in its own right concentrates international discussion between researchers (Dyckhoff et al., 2012). Around 2011, the researchers’ community delivers the first international Conference on Learning Analytics and Knowledge (LAK 2011) and formulates the Society for Learning Analytics Research (SoLAR).  A working definition of LA based on the international discussion "is the measurement, collection, analysis and reporting of data about learners and their contexts, for purposes of understanding and optimizing learning and the environments in which it occurs".

The general objective of LA is to capture learning behaviors in order to decode, interpret and support learning process.  The outcome of LA application can be a valuable tool:

  • for instructors/ teachers:  to provide interpretation of students’ progress
  • for students:  to deliver feedback on their progress
  • for administrators:  to deliver information about the course and management data (grades, status, progress)

 

References

  • Dyckhoff, A. L., Zielke, D., Bültmann, M., Chatti, M. A., & Schroeder, U. (2012).Design and Implementation of a Learning Analytics Toolkit for Teachers. Educational Technology & Society, 15 (3), 58–76.
  • Ferguson, R.(2012). Learning analytics: drivers, developments and challenges. International Journal of Technology Enhanced Learning, 4(5/6) pp. 304–317.
  • Siemens, G. (2010). What are Learning Analytics? Retrieved July 29, 2011, from http://goo.gl/LPrBa
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MOOCs

Published in Glossary

MOOCs

Massive Open Online Courses (MOOCs) are a new term in distance education.  Historically MOOCs have their roots in the movement of Open Educational Resources (OER).  The existence of MOOCs is situated in 2008, where George Siemens and Stephen Downes offered an open online course “Connectivism and Connective Knowledge” in the University of Manitoba, Canada (Tharindu et al., 2013).  In 2012, "The New York Times" coined that it was “the year of the MOOC” and by 2013 MOOC included in the Oxford English Dictionary.

A working definition of a MOOC is illustrated as “an online course open to anyone without restrictions (free of charge and without a limit to attendance), usually structured around a set of learning goals in an area of study, which often runs over a specific period of time (with a beginning and end date) on an online platform which allows interactive possibilities (between peers or between students and instructors) that facilitate the creation of a learning community.  As it is the case for any online course, it provides some course materials and (self) assessment tools for independent studying” (EU, 2013).

There are two main classes of MOOCs (Conole, 2013):

cMOOCs, inspired from the pedagogical theory of connectivism (connectivist-MOOCs).
These courses based on the pedagogical model that support the principles of peer learning, collaboration and social networking.  cMOOCs, run on open source learning platforms and are guided by the academics from different universities (many courses are offered from Athabasca and Manitoba Universities in Canada).  There are examples included: David Wiley’s course on "Open Education", "Personal Learning Environments and Networks (CCK11)",and "Learning Analytics (LAK12)".

xMOOCs, inspired from the pedagogical theory of cognitive-behaviourist approach with more self-paced learning  (eXtension of something else”-MOOCs).
These courses based on the pedagogical model that support the principles of traditional university courses (lecture, instruction, discussion etc.).  xMOOCs, run on proprietary specialist software platforms.  There are technology providers (Udacity, EdX, and Coursera) and prestigious universities (Harvard, Stanford, MITx) that offer their online versions of traditional courses.

 

References

  • Conole, G. (2013)MOOCs as disruptive technologies: strategies for enhancing the learner experience and quality of MOOC, Revista de Educación a Distancia, 2013
  • Tharindu R. Liyanagunawardena, Andrew A. Adams, and Shirley A. Williams. “MOOCs: A Systematic Study of the Published Literature 2008–2012.” International Review of Research in Open and Distance Learning 14 (2013): 201–27.
  • European Commission. “Report on Web Skills Survey: Support Services to Foster Web Talent in Europe by Encouraging the use of MOOCs Focused on web Talent—First Interim Report.” May 2014. Available online: http://goo.gl/0wIibc
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Tangible 3D Tabletop

Published in Glossary

Tangible 3D Tabletop

The roots of tangible 3D tabletops are situated in Tabletop interfaces, which represent multi-touch interfaces and several persons can simultaneously interact directly with a flat surface, using their fingertips.  Towards this a tangible 3D tabletop exploits the potential of tangible tabletop interaction and 3D projection.

This combination offers a new functionality on tangible objects, which can be augmented with visual content on the tabletop.  Its tangible object can be augmented to its physical shape, position, and orientation.

This means that multiple individuals can simultaneously collaborate, manipulate tangibles, use multitouch interactions with the tabletop and visualize the effects of interactions.

 

References

  • Halskov K. & Dalsgaard P. (2013). Projected Play: A Tangible 3D Tabletops, PerDis '13, June 04 - 05 2013, Mountain View, CA, USA
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Bring your own device (BYOD)

Published in Glossary

Bring your own device (BYOD)


Bring your own device (BYOD) is a concept that allows employees in an organization, or students in schools or campus to utilize their personally-owned technology devices so as to access data from, to complete tasks, to interact with peers and to manage their learning. The BYOD concept refers to technology models where individuals bring a personally owned device such as a laptop/desktop computer, a smartphone or a tablet(Alberta Education, 2012).

There is also another broad category, the xYOD which refers to different technology decisions such as HYOD (Here’s Your Own Device) or CYOD (Choose Your Own Device) (Cavoukian, 2013).

References

  • Alberta Education. (2012). Bring your own device: a guide for schools. Edmonton: Alberta Education.
  • Cavoukian A. (2013). BYOD: (Bring Your Own Device) Is Your Organization Ready. Information and Privacy Commissioner, Ontario, Canada
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