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Experimental And Quasi Experimental Designs For Research

One distinctive feature of any adaptive system is the user model that represents essential information about each user This chapter complements other chapters of this book in reviewing user models and user modeling approaches applied in adaptive Web systems The presentation is structured along three dimensions: what is being modeled, how it is modeled, and how the models are maintained After a broad overview of the nature of the information presented in these various user models, the chapter focuses on two groups of approaches to user model representation and maintenance: the overlay approach to user model representation and the uncertainty-based approach to user modeling

User models for adaptive hypermedia and adaptive educational systems

In the last 16 years, more than 200 research articles were published about research-paper recommender systems. We reviewed these articles and present some descriptive statistics in this paper, as well as a discussion about the major advancements and shortcomings and an overview of the most common recommendation concepts and approaches. We found that more than half of the recommendation approaches applied content-based filtering (55 %). Collaborative filtering was applied by only 18 % of the reviewed approaches, and graph-based recommendations by 16 %. Other recommendation concepts included stereotyping, item-centric recommendations, and hybrid recommendations. The content-based filtering approaches mainly utilized papers that the users had authored, tagged, browsed, or downloaded. TF-IDF was the most frequently applied weighting scheme. In addition to simple terms, n-grams, topics, and citations were utilized to model users' information needs. Our review revealed some shortcomings of the current research. First, it remains unclear which recommendation concepts and approaches are the most promising. For instance, researchers reported different results on the performance of content-based and collaborative filtering. Sometimes content-based filtering performed better than collaborative filtering and sometimes it performed worse. We identified three potential reasons for the ambiguity of the results. (A) Several evaluations had limitations. They were based on strongly pruned datasets, few participants in user studies, or did not use appropriate baselines. (B) Some authors provided little information about their algorithms, which makes it difficult to re-implement the approaches. Consequently, researchers use different implementations of the same recommendations approaches, which might lead to variations in the results. (C) We speculated that minor variations in datasets, algorithms, or user populations inevitably lead to strong variations in the performance of the approaches. Hence, finding the most promising approaches is a challenge. As a second limitation, we noted that many authors neglected to take into account factors other than accuracy, for example overall user satisfaction. In addition, most approaches (81 %) neglected the user-modeling process and did not infer information automatically but let users provide keywords, text snippets, or a single paper as input. Information on runtime was provided for 10 % of the approaches. Finally, few research papers had an impact on research-paper recommender systems in practice. We also identified a lack of authority and long-term research interest in the field: 73 % of the authors published no more than one paper on research-paper recommender systems, and there was little cooperation among different co-author groups. We concluded that several actions could improve the research landscape: developing a common evaluation framework, agreement on the information to include in research papers, a stronger focus on non-accuracy aspects and user modeling, a platform for researchers to exchange information, and an open-source framework that bundles the available recommendation approaches.

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Research-paper recommender systems: a literature survey

Gamification of education is a developing approach for increasing learners’ motivation and engagement by incorporating game design elements in educational environments. With the growing popularity of gamification and yet mixed success of its application in educational contexts, the current review is aiming to shed a more realistic light on the research in this field by focusing on empirical evidence rather than on potentialities, beliefs or preferences. Accordingly, it critically examines the advancement in gamifying education. The discussion is structured around the used gamification mechanisms, the gamified subjects, the type of gamified learning activities, and the study goals, with an emphasis on the reliability and validity of the reported outcomes. To improve our understanding and offer a more realistic picture of the progress of gamification in education, consistent with the presented evidence, we examine both the outcomes reported in the papers and how they have been obtained. While the gamification in education is still a growing phenomenon, the review reveals that (i) insufficient evidence exists to support the long-term benefits of gamification in educational contexts; (ii) the practice of gamifying learning has outpaced researchers’ understanding of its mechanisms and methods; (iii) the knowledge of how to gamify an activity in accordance with the specifics of the educational context is still limited. The review highlights the need for systematically designed studies and rigorously tested approaches confirming the educational benefits of gamification, if gamified learning is to become a recognized instructional approach.

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Gamifying education: what is known, what is believed and what remains uncertain: a critical review

A systematic review of gamification in e-Health

Introduction Traditional schooling is perceived as ineffective and boring by many students. Although teachers continuously seek novel instructional approaches, it is largely agreed that today's schools face major problems around student motivation and engagement (Lee & Hammer, 2011). The use of educational games as learning tools is a promising approach due to the games' abilities to teach and the fact that they reinforce not only knowledge but also important skills such as problem-solving, collaboration, and communication. Games have remarkable motivational power; they utilize a number of mechanisms to encourage people to engage with them, often without any reward, just for the joy of playing and the possibility to win. Creating a highly engaging, full-blown instructional game however is difficult, time consuming, and costly (Kapp, 2012a), while typically targeting only a single set of learning objectives as chosen by the game designer. In addition, their effective classroom adoption requires certain technical infrastructure and appropriate pedagogical integration. As opposed to using elaborate games requiring a large amount of design and development efforts, the "gamification" approach suggests using game thinking and game design elements to improve learners' engagement and motivation. Gamification, defined by Deterding et al. (2011) as the use of game design elements in non-game contexts, is a fairly new and rapidly growing field. The concept of gamification is different from that of an educational or serious game. While the latter describes the design of full-fledged games for non-entertainment purposes, "gamified" applications merely employ elements of games. The term "gamification" is quite recent: According to (Deterding et al., 2011) its first documented use is in 2008 but it did not see widespread adoption before the second half of 2010. Nevertheless, the concept itself is not new. For example, badges and ranks have been long used in the military, in the early Soviet era, game elements were used by the Soviet Union leaders as a substitute for monetary incentives for performing at work, etc. In recent years gamification has seen rapid adoption in business, marketing, corporate management, and wellness and ecology initiatives. This is driven by its potential to shape users' behavior in a desirable direction. Loyalty programs such as the frequent-flyer programs, Foursquare, and Nike+ are often given as examples of successful gamified mass-market products. Stackoverflow.com provides another example in which users' reputations increase as they answer questions and receive votes for their answers. Online education sites such as codeacademy.com and khanacademy.org use game elements to better engage users. The more courses and lessons that users complete, the more badges they earn. Sites like eBay and Fitocracy use game elements to keep people engaged and to encourage friendly competition between users. Gamification is still rising in popularity. According to Gartner's Hype Cycle (Gartner, 2013), a research methodology that outlines an emerging technology's viability for commercial success, gamification is at the peak of the Hype Cycle in 2013, with an expectation for reaching the productivity plateau in five to ten years. This position, however, mainly reflects its use in business contexts. The penetration of the gamification trend in educational settings seems to be still climbing up to the top, as indicated by the amount and annual distribution of the reviewed works. This paper presents the results of a study of the published works on the application of gamification to education, which aims to shed light on the tendencies and emerging practices in this area. There are few literature reviews on gamification (see Xu, 2012; Hamari, Koivisto, & Sarsa, 2014; Nah, Zeng, Telaprolu, Ayyappa, & Eschenbrenner, 2014), with only the last one focusing on education. This study differs from the latter by presenting a thematic analysis instead of narrative summaries that focus on a qualitative review. …

Gamification in Education: A Systematic Mapping Study

The big question for many researchers in the area of educational systems now is what is the next step in the evolution of e-learning? Are we finally moving from a scattered intelligence to a coherent space of collaborative intelligence? How close we are to the vision of the Educational Semantic Web and what do we need to do in order to realize it? Two main challenges can be seen in this direction: on the one hand, to achieve interoperability among various educational systems and on the other hand, to have automated, structured and unified authoring support for their creation. In the spirit of the Semantic Web a key to enabling the interoperability is to capitalize on the (1) semantic conceptualization and ontologies, (2) common standardized communication syntax, and (3) large-scale service-based integration of educational content and functionality provision and usage. A central role in achieving unified authoring support plays the process-awareness of authoring tools, which should reflect the semantic evolution of e-learning systems. The purpose of this paper is to outline the state-of-the-art research along those lines and to suggest a realistic way towards the Educational Semantic Web. With regard to the latter we first propose a modular semantic-driven and service-based interoperability framework, in order to open up, share and reuse educational systems’ content and knowledge components. Then we focus on content creation by proposing ontology-driven authoring tools that reflect the modularization in the educational systems, maintain a consistent view on the entire authoring process, and provide wide (semi-) automation of the complex authoring tasks.

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The New Challenges for E-learning: The Educational Semantic Web

Ontologies and Semantic Web for E-Learning

Learning is a goal driven social activity determined by motivational factors. To be able to efficiently gamify learning for improved student motivation and engagement, the educators have to understand the related aspects studied in games, motivational psychology and pedagogy. This will help them to identify the factors that drive and explain desired learning behaviors. This paper presents a survey of the main approaches employed in gamification and the emerging new directions in the context of the relevant motivational psychology and pedagogy. The focus is on the motivational factors that impact learning and understanding of behavior change. The purpose of the paper is two-fold: on one side, to provide analysis and guide to relevant works related to gamification along with outlining the emerging trends, and on the other, to provide foundation for evaluation and identification of the areas of possible improvements.

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Darina Dicheva

Papers

Gamification in Education: A Systematic Mapping Study

Gamifying education: what is known, what is believed and what remains uncertain: a critical review

The New Challenges for E-learning: The Educational Semantic Web

Ontologies and Semantic Web for E-Learning

From Gamification to Gameful Design and Gameful Experience in Learning