identifying archaeological knowledge using multi dimensional scaling and multiple constraint satisfaction

In this thesis, I look at the current state of research in two fields: the cognitive psychology of learning and expertise & the development of Intelligent Tutoring Systems, especially their methods of modelling the users knowledge state. Within these areas I proceed to examine the way that these theories have overlapped in the past and consider their recent divergence, suggesting that this parting of the ways is premature. I then consider other relevent research so as to suggest a hypothesis where a symbolic connectionist approach to the modelling of knowledge states could be a solution to previous difficulties in the field of Intelligent Tutoring. This hypothesis is then used to construct a method for its examination and also a computer program to analyse the collected data. I then undertake experimental work to validate my hypothesis, and compare my results and methods with a pre-established technique for interpreting the data, that of multi-dimensional scaling. Finally the method now shown to be feasible is discussed to indicate the its success and highlight its shortcomings. Further suggestions are also made as to further research avenues

Light-weight ontologies for scrutable user modelling

This thesis is concerned with the ways light-weight ontologies can support scrutability for large user models and the user modelling process. It explores the role that light-weight ontologies can play, and how they can be exploited, for the purpose of creating and maintaining large, scrutable user models consisting of hundreds of components. We address problems in four key areas: ontology creation, metadata annotation, creation and maintenance of large user models, and user model visualisation, with a goal to provide a simple and adaptable approach that maintains scrutability. Each of these key areas presents a number of challenges that we address. Our solution is the development of a toolkit, LOSUM, which consists of a number of tools to support the user modelling process. It incorporates light-weight ontologies to fulfill a number of roles: aiding in metadata creation, providing structure for large user model visualisation, and as a means to reason across granularities in the user model. In conjunction with this, LOSUM also features a novel visualisation tool, SIV, which performs a dual role of ontology and user model visualisation, supporting the process of ontology creation, metadata annotation, and user model visualisation. We evaluated our approach at each stage with small user studies, and conducted a large scale integrative evaluation of these approaches together in an authentic learning context with 114 students, of whom 77 had exposure to their learner models through SIV. The results showed that students could use the interface and understand the process of user model construction. The flexibility and adaptability of the toolkit has also been demonstrated in its deployment in several other application areas

Proceedings of the International Workshop on EuroPLOT Persuasive Technology for Learning, Education and Teaching (IWEPLET 2013)

"This book contains the proceedings of the International Workshop on EuroPLOT Persuasive Technology for Learning, Education and Teaching (IWEPLET) 2013 which was held on 16.-17.September 2013 in Paphos (Cyprus) in conjunction with the EC-TEL conference. The workshop and hence the proceedings are divided in two parts: on Day 1 the EuroPLOT project and its results are introduced, with papers about the specific case studies and their evaluation. On Day 2, peer-reviewed papers are presented which address specific topics and issues going beyond the EuroPLOT scope. This workshop is one of the deliverables (D 2.6) of the EuroPLOT project, which has been funded from November 2010 – October 2013 by the Education, Audiovisual and Culture Executive Agency (EACEA) of the European Commission through the Lifelong Learning Programme (LLL) by grant #511633. The purpose of this project was to develop and evaluate Persuasive Learning Objects and Technologies (PLOTS), based on ideas of BJ Fogg. The purpose of this workshop is to summarize the findings obtained during this project and disseminate them to an interested audience. Furthermore, it shall foster discussions about the future of persuasive technology and design in the context of learning, education and teaching. The international community working in this area of research is relatively small. Nevertheless, we have received a number of high-quality submissions which went through a peer-review process before being selected for presentation and publication. We hope that the information found in this book is useful to the reader and that more interest in this novel approach of persuasive design for teaching/education/learning is stimulated. We are very grateful to the organisers of EC-TEL 2013 for allowing to host IWEPLET 2013 within their organisational facilities which helped us a lot in preparing this event. I am also very grateful to everyone in the EuroPLOT team for collaborating so effectively in these three years towards creating excellent outputs, and for being such a nice group with a very positive spirit also beyond work. And finally I would like to thank the EACEA for providing the financial resources for the EuroPLOT project and for being very helpful when needed. This funding made it possible to organise the IWEPLET workshop without charging a fee from the participants.

The Effects of Displayed Violence and Game Speed in First-Person Shooters on Physiological Arousal and Aggressive Behavior

Many studies have been conducted to examine the effects of displayed violence in digital games on outcomes like aggressive behavior and physiological arousal. However, they often lack a proper manipulation of the relevant factors and control of confounding variables. In this study, the displayed violence and game speed of a recent first-person shooter game were varied systematically using the technique of modding, so that effects could be explained properly by the respective manipulations. Aggressive behavior was measured with the standardized version of the Competitive Reaction Time Task or CRTT (Ferguson et al., 2008}. Physiological arousal was operationalized with four measurements: galvanic skin response (GSR), heart rate (HR), body movement, force on mouse and keyboard. A total of N = 87 participants played in one of four game conditions (low- vs. high-violence, normal- vs. high speed) while physiological measurements were taken with finger clips, force sensors on input devices (mouse and keyboard), and a Nintendo Wii balance board on the chair they sat on. After play, their aggressive behavior was measured with the CRTT. The results of the study do not support the hypothesis that playing digital games increases aggressive behavior. There were no significant differences in GSR and HR, but with a higher game speed, participants showed less overall body movement, most likely to meet the game’s higher demands on cognitive and motor capacities. Also, higher game speed and displayed violence caused an increase in applied force on mouse and keyboard. Previous experience with digital games did not moderate any of these findings. Moreover, it provides further evidence that the CRTT should only be used in a standardized way as a measurement for aggression, if at all. Using all 7 different published (though not validated) ways to calculate levels of aggression from the raw data, “evidence” was found that playing a violent digital game increases, decreases, or does not change aggression at all. Thus, the present study does extend previous research. Firstly, it shows the methodological advantages of modding in digital game research to accomplish the principles of psychological (laboratory) experiments by manipulating relevant variables and controlling all others. It also demonstrates the test-theoretical problems of the highly diverse use of the CRTT. It provides evidence that for a meaningful interpretation of effects of displayed violence in digital games, there are other game characteristics that should be controlled for since they might have an effect on relevant outcome variables. Further research needs to identify more of those game features, and it should also improve the understanding of the different measures for physiological arousal and their interrelatedness

LEARNING IN SHORT BURSTS: A CONTENT ANALYSIS OF PROFESSIONAL DEVELOPMENT MICROLEARNING VIDEOS

D.Ed

Analyzing Interaction Patterns to Verify a Simulation/Game Model

Thesis (Ph.D.) - Indiana University, School of Education, 2012In order for simulations and games to be effective for learning, instructional designers must verify that the underlying computational models being used have an appropriate degree of fidelity to the conceptual models of their real-world counterparts. A simulation/game that provides incorrect feedback is likely to promote misunderstanding and adversely affect learning and transfer. Numerous methods for verifying the accuracy of a computational model exist, but it is generally accepted that no single method is adequate and that multiple methods should be used. The purpose of this study was to propose and test a new method for collecting and analyzing users' interaction data (e.g., choices made, actions taken, results and feedback obtained) to provide quantified evidence that the underlying computational model of a simulation/game represents the conceptual model with sufficient accuracy. In this study, analysis of patterns in time (APT) was used to compare gameplay results from the Diffusion Simulation Game (DSG) with predictions based on diffusion of innovations theory (DOI). A program was written to automatically play the DSG by analyzing the game state during each turn, seeking patterns of game component attributes that matched optimal strategies based on DOI theory. When the use of optimal strategies did not result in the desired number of successful games, here defined as the threshold of confidence for model verification, further investigation revealed flaws in the computational model. These flaws were incrementally corrected and subsequent gameplay results were analyzed until the threshold of confidence was achieved. In addition to analysis of patterns in time for model verification (APTMV), other verification methods used included code walkthrough, execution tracing, desk checking, syntax checking, and statistical analysis. The APTMV method was found to be complementary to these other methods, providing quantified evidence of the computational model's degree of accuracy and pinpointing flaws that could be corrected to improve fidelity. The APTMV approach to verification and improvement of computational models is described and compared with other methods, and improvements to the process are proposed

Studies of visual attention in physics problem solving

Doctor of PhilosophyDepartment of PhysicsN. Sanjay RebelloThe work described here represents an effort to understand and influence visual attention while solving physics problems containing a diagram. Our visual system is guided by two types of processes -- top-down and bottom-up. The top-down processes are internal and determined by ones prior knowledge and goals. The bottom-up processes are external and determined by features of the visual stimuli such as color, and luminance contrast. When solving physics problems both top-down and bottom-up processes are active, but to varying degrees. The existence of two types of processes opens several interesting questions for physics education. For example, how do bottom-up processes influence problem solvers in physics? Can we leverage these processes to draw attention to relevant diagram areas and improve problem-solving? In this dissertation we discuss three studies that investigate these open questions and rely on eye movements as a primary data source. We assume that eye movements reflect a person’s moment-to-moment cognitive processes, providing a window into one’s thinking. In our first study, we compared the way correct and incorrect solvers viewed relevant and novice-like elements in a physics problem diagram. We found correct solvers spent more time attending to relevant areas while incorrect solvers spent more time looking at novice-like areas. In our second study, we overlaid these problems with dynamic visual cues to help students’ redirect their attention. We found that in some cases these visual cues improved problem-solving performance and influenced visual attention. To determine more precisely how the perceptual salience of diagram elements influenced solvers’ attention, we conducted a third study where we manipulated the perceptual salience of the diagram elements via changes in luminance contrast. These changes did not influence participants’ answers or visual attention. Instead, similar to our first study, the time spent looking in various areas of the diagram was related to the correctness of an answer. These results suggest that top-down processes dominate while solving physics problems. In sum, the study of visual attention and visual cueing in particular shows that attention is an important component of physics problem-solving and can potentially be leveraged to improve student performance