A review of privacy and usability issues in mobile health systems: Role of external factors

The increased penetration of mobile devices has created opportunities in the health sector and led to emerging of mobile health systems. As much as the mobile health systems have registered tremendous progress, they have been faced with privacy and usability issues. Due to the sensitivity of health information, there is an ethical need to equip mobile health systems with adequate privacy measures. However, these systems should also be useable by the intended users. Even though many researchers are working on solutions, the issues still persist. External factors such as cultural differences have also contributed to the issues, yet they have been under researched. In this article, we conduct a systematic literature review of 22 articles, categorize and present privacy and usability issues and possible solutions. We then discuss the relevance and implications of external factors to the findings on privacy and usability. We end with recommendations to address these external factors.Peer Reviewe

Situation Creator: A Pedagogical Agent Creating Learning Opportunities

Miao, Y., Hoppe, H. U., & Pinkwart, N. (2007). Situation Creator: A Pedagogical Agent Creating Learning Opportunities. In R. Luckin, K. Koedinger & J. Greer (Eds.), Proceedings of the 13th International Conference on Artificial Intelligence in Education (pp. 614-617). Amsterdam, The Netherlands: IOS Press.In a multi-user, real-time, and situation-based learning environment, the availability of enough and appropriate situations is crucial for success. In order to improve effectiveness and efficiency of learning, we develop a new type of pedagogical agent: situation creator. Such an agent intentionally creates specific situations in the shared virtual driving place according to users’ performance information. We conduct a pilot evaluation and found that the situation creators significantly increase the number of situations that a learner can expect to encounter while using the system

A Collaborative Virtual Environment for Situated Learning of Car Driving

In the view of situated learning theory, knowledge and understanding are fundamentally products of learning situations. Learning is situated and takes place by means of legitimate peripheral participation within the context of a community of practice. Based on the theory of situated learning, this article develops conceptual and technical approaches to build a web-based collaborative 3D car-driving simulation environment that requires only low computing, networking and development resources. Rather than instructing individuals on a formal, structured, intensive and programmed base, this simulation environment supports members of virtual communities of practice to perform informal, unstructured, spontaneous, collaborative, situated learning. Pilot studies conducted with the system show its partial success and demonstrate that it depends on the characteristics of specific educationally valuable learning situations whether the collaborative learning approach we propose can succeed also with smaller group sizes

A Collaborative Virtual Environment for Situated Learning of Car Driving

Miao, Y., Pinkwart, N., and Hoppe, H.U. (2006). "A Collaborative Virtual Environment for Situated Learning of Car Driving". International Journal on Advanced Technology for Learning (ATL), 3(4), 233-240.In the view of situated learning theory, knowledge and understanding are fundamentally products of learning situations. Learning is situated and takes place by means of legitimate peripheral participation within the context of a community of practice. Based on the theory of situated learning, this article develops conceptual and technical approaches to build a web-based collaborative 3D car-driving simulation environment that requires only low computing, networking and development resources. Rather than instructing individuals on a formal, structured, intensive and programmed base, this simulation environment supports members of virtual communities of practice to perform informal, unstructured, spontaneous, collaborative, situated learning. Pilot studies conducted with the system show its partial success and demonstrate that it depends on the characteristics of specific educationally valuable learning situations whether the collaborative learning approach we propose can succeed also with smaller group sizes

Ein Autorenwerkzeug zur Konfiguration von eLearning-Argumentationsframeworks

Argumentationsfertigkeiten sind essentiell in vielen Bereichen des Lebens. Dies gilt sowohl auf privater als auch auf geschäftlicher Ebene. Daher spielt die Ausbildung von Argumentations-fertigkeiten eine zentrale Rolle. Eine Möglichkeit, diese Ausbildung zu unterstützen, sind com-puterbasierte Argumentationssysteme, die sich jedoch oftmals als zu unflexibel für den Einsatz über Domänengrenzen hinweg herausgestellt haben. Dieser Beitrag beschreibt das für ver-schiedene Domänen speziell konfigurierbare LASAD Argumentationsframework und zeigt, dass komplexe Konfigurationsmechanismen durch entsprechende Hilfsmittel beherrschbar bleiben können

Adaptive Rückmeldungen im intelligenten Tutorensystem LARGO

The Intelligent Tutoring System LARGO is designed to help law students learn argumentation skills. The approach implemented in LARGO uses transcripts of oral arguments as learning resources: Students annotate them and create graphical representations of the argument flow. The system encourages students to reflect upon arguments proposed by the attorneys and helps students detect possible weaknesses in their analysis of the dispute. Technically, graph grammar and collaborative filtering algorithms are employed to detect these weaknesses. This article describes how “usage contexts” are determined and used to create adaptive feedback in LARGO. On the basis of a controlled study with the system that took place with law students at the University of Pittsburgh, we discuss to what extent the automatically calculated usage contexts can predict student’s learning gains

An Ensemble Method to Predict Student Performance in an Online Math Learning Environment

ABSTRACT The number of e-learning platforms and blended learning environments is continuously increasing and has sparked a lot of research around improvements of educational processes. Here, the ability to accurately predict student performance plays a vital role. Previous studies commonly focused on the construction of predictors tailored to a formal course. In this paper we relax this constraint, leveraging domain knowledge and combining a knowledge graph representation with activity scopes based on sets of didactically feasible learning objectives. Specialized scope classifiers are then combined to an ensemble to robustly predict student performance on learning objectives independently of the student's individual learning setting. The final ensemble's accuracy trumps any single classifier tested

A review of technologies for collaborative online information seeking: On the contribution of collaborative argumentation

In everyday life, people seek, evaluate, and use online sources to underpin opinions and make decisions. While education must promote the skills people need to critically question the sourcing of online information, it is important, more generally, to understand how to successfully promote the acquisition of any skills related to seeking online information. This review outlines technologies that aim to support users when they collaboratively seek online information. Upon integrating psychological–pedagogical approaches on trust in and the sourcing of online information, argumentation, and computer-supported collaborative learning, we reviewed the literature (N = 95 journal articles) on technologies for collaborative online information seeking. The technologies we identified either addressed collaborative online information seeking as an exclusive process for searching for online information or, alternatively, addressed online information seeking within the context of a more complex learning process. Our review was driven by three main research questions: We aimed to understand whether and how the studies considered 1) the role of trust and critical questioning in the sourcing of online information, 2) the learning processes at play when information seekers engage in collaborative argumentation, and 3) what affordances are offered by technologies that support users’ collaborative seeking of online information. The reviewed articles that focused exclusively on technologies for seeking online information primarily addressed aspects of cooperation (e.g., task management), whereas articles that focused on technologies for integrating the processes of information seeking into the entire learning processes instead highlighted aspects of collaborative argumentation (e.g., exchange of multiple perspectives and critical questioning in argumentation). Seven of the articles referred to trust as an aspect of seekers’ sourcing strategies. We emphasize how researchers’, users’, and technology developers’ consideration of collaborative argumentation could expand the benefits of technological support for seeking online information.Peer Reviewe

A conceptual graph-based model of creativity in learning

Teaching creativity is one of the key goals of modern education. Yet, promoting creativity in teaching remains challenging, not least because creative achievement is contingent on multiple factors, such as prior knowledge, the classroom environment, the instruction given, and the affective state of the student. Understanding these factors and their interactions is crucial for successfully integrating creativity in teaching. However, keeping track of all factors and interactions on an individual student level may well exceed the capacity of human teachers. Artificial intelligence techniques may thus prove helpful and necessary to support creativity in teaching. This paper provides a review of the existing literature on creativity. More importantly, the review is distilled into a novel, graph-based model of creativity with three target audiences: Educators, to gain a concise overview of the research and theory of creativity; educational researchers, to use the interactions predicted by theory to guide experimental design; and artificial intelligence researchers, who may use parts of the model as a starting point for tools which measure and facilitate creativity.Peer Reviewe