Ulrik Schroeder

A reference model for learning analytics

Recently, there is an increasing interest in learning analytics in Technology-Enhanced Learning TEL. Generally, learning analytics deals with the development of methods that harness educational datasets to support the learning process. Learning analytics LA is a multi-disciplinary field involving machine learning, artificial intelligence, information retrieval, statistics and visualisation. LA is also a field in which several related areas of research in TEL converge. These include academic analytics, action analytics and educational data mining. In this paper, we investigate the connections between LA and these related fields. We describe a reference model for LA based on four dimensions, namely data and environments what?, stakeholders who?, objectives why? and methods how?. We then review recent publications on LA and its related fields and map them to the four dimensions of the reference model. Furthermore, we identify various challenges and research opportunities in the area of LA in relation to each dimension.

What Drives a Successful MOOC? An Empirical Examination of Criteria to Assure Design Quality of MOOCs

Massive Open Online Courses (MOOCs) have gained a lot of attention in the last years as a new technology enhanced learning (TEL) approach in higher education. MOOCs provide more educational opportunities to a massive number of learners to attend free online courses around the globe. Discussions around MOOCs have been focusing on the potential, social, institutional, technological, relevance, and marketing issues and less on the quality design of MOOC environments. Several studies have reported a high drop-out rate in average of 95% of course participants and other pedagogical problems concerning assessment and feedback. Thus, the quality of MOOCs design is worth additional investigation. Although several studies identified a large set of criteria to the successful design of TEL systems in general, not all of them can be used in the MOOC context, due to some unique features of MOOCs. This study is a first step towards identifying specific criteria that need to be considered when designing and implementing MOOCs. The results of this empirical study are based on a large survey targeting learners as well as professors, both with MOOC experience. As a result, we identified and rated 74 indicators classified into our two main dimensions of pedagogical and technological criteria distributed over six categories. From these, the learning analytics and assessment categories were found to be the key features for effective MOOCs.

Increase Physical Fitness and Create Health Awareness through Exergames and Gamification - The Role of Individual Factors, Motivation and Acceptance.

Demographic change and the aging population push health and welfare system to its limits. Increased physical fitness and increased awareness for health issues will help elderly to live independently for longer and will thereby reduce the costs in the health care system. Exergames seem to be a promising solution for promoting physical fitness. Still, there is little evidence under what conditions Exergames will be accepted and used by elderly. To investigate promoting and hindering factors we conducted a user study with a prototype of an Exergame. We contrasted young vs. elderly players and investigated the role of gamer types, personality factors and technical expertise on the performance within the game and changes in the attitude towards individual health after the game. Surprisingly, performance within the game is not affected by performance motivation but by gamer type. More importantly, a universal positive effect on perceived pain is detected after the Exergame intervention.

From boring to scoring - a collaborative serious game for learning and practicing mathematical logic for computer science education

In this study, we address the problem of low retention and high dropout rates of computer science university students in early semesters of the studies. Complex and high abstract mathematical learning materials have been identified as one reason for the dropout rate. In order to support the understanding and practicing of core mathematical concepts, we developed a game-based multitouch learning environment in which the need for a suitable learning environment for mathematical logic was combined with the ability to train cooperation and collaboration in a learning scenario. As application domain, the field of mathematical logic had been chosen. The development process was accomplished along three steps: First, ethnographic interviews were run with 12 students of computer science revealing typical problems with mathematical logic. Second, a multitouch learning environment was developed. The game consists of multiple learning and playing modes in which teams of students can collaborate or compete against each other. Finally, a twofold evaluation of the environment was carried out (user study and cognitive walk-through). Overall, the evaluation showed that the game environment was easy to use and rated as helpful: The chosen approach of a multiplayer game supporting competition, collaboration, and cooperation is perceived as motivating and “fun.”

LaaN: Convergence of Knowledge Management and Technology-Enhanced Learning

Knowledge Management (KM) and Technology-Enhanced Learning (TEL) have attracted attention over the past two decades and are meanwhile considered as important means to increase individual and organizational performance. There is, however, a wide agreement that traditional KM and TEL models have failed to cope with the fast-paced change and critical challenges of the new knowledge era. In this paper, we propose a vision for future KM/TEL approaches which aims to fulfill the needs of the new knowledge landscape by introducing the Learning as a Network (LaaN) theory as a new learning theory characterized by the convergence of KM and TEL within a learner-centric knowledge environment. We further discuss a possible implementation of the LaaN theory based on the personal learning environment (PLE) concept.

Animated demonstrations and training wheels interfaces in a complex learning environment

Learning how to use a new software program can be a difficult and demanding task, especially for novices. There are several types of support for users exploring a software package. Animated demonstrations show how experts use an application, and training wheels interfaces offer a secure environment for exploration. To support different types of learners, external help should be adapted according to learner characteristics. The study presented in this article investigates effects of different support types in combination with the computer self-efficacy of learners. Young students (8th graders) were supported with text manuals, animated demonstrations, or animated demonstrations combined with a training wheels interface. In this context, they had to solve problems in physics and mathematics with a spreadsheet program. Results showed that animated demonstrations outperformed text manuals in many cases. Training wheels interfaces seemed to have disadvantages compared to unmodified user interfaces. In addition, motivational aspects have been investigated. Subjects with high computer self-efficacy scores were more motivated than their counterparts. Statistics (analysis of variance) revealed no interaction effects between the treatment and computer self-efficacy.

Tag-Based Collaborative Filtering Recommendation in Personal Learning Environments

The personal learning environment (PLE) concept offers a learner-centric view of learning and suggests a shift from knowledge-push to knowledge-pull approach to learning. One concern with a PLE-driven knowledge-pull approach to learning, however, is information overload. Recommender systems can provide an effective mechanism to deal with the information overload problem in PLEs. In this paper, we study different tag-based collaborative filtering recommendation techniques on their applicability and effectiveness in PLE settings. We implement 16 different tag-based collaborative filtering recommendation algorithms, memory based as well as model based, and compare them in terms of accuracy and user satisfaction. The results of the conducted offline and user evaluations reveal that the quality of user experience does not correlate with high-recommendation accuracy.

Mobile learning in context

The widespread use of mobile technologies has led to an increasing interest in mobile learning. Context is a central topic of research in that area. In fact, a major benefit of mobile devices is that they enable learning across contexts. In this paper, we explore how context can deliver significant benefits in mobile learning and provide an extensive review of the current literature and research on mobile learning in context. Furthermore, we identify various challenges and research opportunities in this area and propose the conceptual framework CAMeL for context-aware mobile learning.

Model-driven mashup personal learning environments

Mashups have become the driving force behind the development of personal learning environments (PLEs). Creating mashups in an ad hoc manner is, however, for end users with little or no programming background not an easy task. Various tools and platforms have been built in an attempt to support mashup creation. These platforms, however, are still considered complex and do not address crucial challenges in mashup development today, such as scalability, interoperability, reuse, and automatic service invocation and mediation. In this paper, we leverage the possibility to use the concept of model-driven mashup development (MDMD) as an approach that can drastically tackle the aforementioned issues and drive the rapid and user-friendly creation of mashups. We then present the conceptual and technical details of PLEF-Ext as a flexible framework for end-user, model-driven development (MDD) of mashup PLEs.

Effects of Aging and Domain Knowledge on Usability in Small Screen Devices for Diabetes Patients

Technology acceptance has become a key concept for the successful rollout of technical devices. Though the concept is intensively studied for nearly 20 years now, still, many open questions remain. This especially applies to technology acceptance of older users, which are known to be very sensitive to suboptimal interfaces and show considerable reservations towards the usage of new technology. Mobile small screen technology increasingly penetrates health care and medical applications. This study investigates impacts of aging, technology expertise and domain knowledge on user interaction using the example of diabetes. For this purpose user effectiveness and efficiency have been measured on a simulated small screen device and related to user characteristics, showing that age and technology expertise have a big impact on usability of the device. Furthermore, impacts of user characteristics and success during the trial on acceptance of the device were surveyed and analyzed.