Behavior Effect of Hint Selection Penalties and Availability in an Intelligent Tutoring System

Proceedings of: Tenth International Confererence on Intelligent Tutoring Systems: Bridges to Learning (ITS 2010). Pittsburg, USA, June 14-18, 2010.his paper presents empirical results about the behavior effect of two different hinting strategies applied on exercises within an ITS: having some penalty on the scoring for viewing hints or not having any effect on the scoring; and hints directly available or only available as a result to an incorrect attempt. We analyze the students' behavior differences when these hinting techniques changed, taking into account the type and difficulty of the presented exercises.Work partially funded by the Learn3 project TIN2008-05163/TSI within the Spanish “Plan Nacional de I+D+I”, and the Madrid regional community project eMadrid S2009/TIC-1650.Publicad

Towards the Prediction of User Actions on Exercises with Hints Based on Survey Results

Proceedings of: 6th European Conference of Technology Enhanced Learning, EC-TEL 2011, Palermo, Italy, September 20-23, 2011.The actions a user performs on exercises depending on the different hinting techniques applied, can be used to adapt future exercises. In this paper, we propose a survey for users in order to know their different actions depending on different conditions. The analysis of preliminary results for some questions of the model shows that there is a correlation between some survey questions and the real student actions, but there is a case in which there is not such correlation. For the cases where that correlation exists, this correlation leads to think that some prediction of users actions based on survey results is possible.Work partially funded by the Learn3 project TIN2008-05163/TSI within the Spanish “Plan Nacional de I+D+I”, and the Madrid regional community project eMadrid S2009/TIC-1650

Analyzing collaborative learning processes automatically

In this article we describe the emerging area of text classification research focused on the problem of collaborative learning process analysis both from a broad perspective and more specifically in terms of a publicly available tool set called TagHelper tools. Analyzing the variety of pedagogically valuable facets of learners’ interactions is a time consuming and effortful process. Improving automated analyses of such highly valued processes of collaborative learning by adapting and applying recent text classification technologies would make it a less arduous task to obtain insights from corpus data. This endeavor also holds the potential for enabling substantially improved on-line instruction both by providing teachers and facilitators with reports about the groups they are moderating and by triggering context sensitive collaborative learning support on an as-needed basis. In this article, we report on an interdisciplinary research project, which has been investigating the effectiveness of applying text classification technology to a large CSCL corpus that has been analyzed by human coders using a theory-based multidimensional coding scheme. We report promising results and include an in-depth discussion of important issues such as reliability, validity, and efficiency that should be considered when deciding on the appropriateness of adopting a new technology such as TagHelper tools. One major technical contribution of this work is a demonstration that an important piece of the work towards making text classification technology effective for this purpose is designing and building linguistic pattern detectors, otherwise known as features, that can be extracted reliably from texts and that have high predictive power for the categories of discourse actions that the CSCL community is interested in

Participatory design to lower the threshold for intelligent support authoring

One of the fundamental aims of authoring tools is to provide teachers with opportunities to configure, modify and generally appropriate the content and pedagogical strategies of intelligent systems. Despite some progress in the field, there is still a need for tools that have low thresholds in terms of the users’ technical expertise. Here, we demonstrate that designing systems with lower entry barrier can potentially be achieved through co-design activities with non-programmers and carefully observing novices. Following an iterative participatory co-design cycle with teachers who have little or no programming expertise, we reflect on their proposed enhancements. Our investigations focus on Authelo, an authoring tool that has been designed primarily for Exploratory Learning Objects, but we conclude the paper by providing transferable lessons, particularly the strong preference for visual interfaces and high-level pedagogical predicates for authoring analysis and feedback rules

Opening Up an Intelligent Tutoring System Development Environment for Extensible Student Modeling

ITS authoring tools make creating intelligent tutoring systems more cost effective, but few authoring tools make it easy to flexibly incorporate an open-ended range of student modeling methods and learning analytics tools. To support a cumulative science of student modeling and enhance the impact of real-world tutoring systems, it is critical to extend ITS authoring tools so they easily accommodate novel student modeling methods. We report on extensions to the CTAT/Tutorshop architecture to support a plug-in approach to extensible student modeling, which gives an author full control over the content of the student model. The extensions enhance the range of adaptive tutoring behaviors that can be authored and support building external, student- or teacher-facing real-time analytics tools. The contributions of this work are: (1) an open architecture to support the plugging in, sharing, re-mixing, and use of advanced student modeling techniques, ITSs, and dashboards; and (2) case studies illustrating diverse ways authors have used the architecture

Gaming the system:Practices against the algorithmic makeover of everyday life

The introduction of technical, algorithmically-controlled interactive medial systems into virtually all contexts of everyday life is a relatively recent phenomenon. Implications, for instance, for social and political contexts are still emerging. One probably unexpected but certainly unintended effect is the emergence of gaming the system behaviours. Gaming is seen here as participants taking advantage of systems by interacting with them in unintended ways to gain unjustified benefits. These behaviours are regularly seen as problematic, and measures to prevent or to detect and to react to them are discussed in the academic discourse. This study aims to establish characteristics, practices and causes of such behaviours, exemplatory in the area of interactive, educational tutoring systems. The study is informed by positions from Game Studies, Cognitive Evaluation Theory (CET; Deci, Ryan) and the (post-) phenomenological discourse on the intentionality of non-human actors. It finds that users feel disenfranchised rather than empowered by the intentionality embodied in algorithmic systems; that those systems afford play; and that gaming behaviour can be read as defensive and evasive, rather than aggressive and criminal.The introduction of technical, algorithmically-controlled interactive medial systems into virtually all contexts of everyday life is a relatively recent phenomenon. Implications, for instance, for social and political contexts are still emerging. One probably unexpected but certainly unintended effect is the emergence of gaming the system behaviours. Gaming is seen here as participants taking advantage of systems by interacting with them in unintended ways to gain unjustified benefits. These behaviours are regularly seen as problematic, and measures to prevent or to detect and to react to them are discussed in the academic discourse. This study aims to establish characteristics, practices and causes of such behaviours, exemplatory in the area of interactive, educational tutoring systems. The study is informed by positions from Game Studies, Cognitive Evaluation Theory (CET; Deci, Ryan) and the (post-) phenomenological discourse on the intentionality of non-human actors. It finds that users feel disenfranchised rather than empowered by the intentionality embodied in algorithmic systems; that those systems afford play; and that gaming behaviour can be read as defensive and evasive, rather than aggressive and criminal

Similarity, precedent and argument from analogy

In this paper, it is shown (1) that there are two schemes for argument from analogy that seem to be competitors but are not, (2) how one of them is based on a distinctive type of similarity premise, (3) how to analyze the notion of similarity using story schemes illustrated by some cases, (4) how arguments from precedent are based on arguments from analogy, and in many instances arguments from classification, and (5) that when similarity is defined by means of episode schemes, we can get a clearer idea of how it integrates with the use of argument from classification and argument from precedent in case-based reasoning by using a dialogue structure

Do optional activities matter in virtual learning environments?

Virtual Learning Environments (VLEs) provide students with activi-ties to improve their learning (e.g., reading texts, watching videos or solving exercises). But VLEs usually also provide optional activities (e.g., changing an avatar profile or setting goals). Some of these have a connection with the learn-ing process, but are not directly devoted to learning concepts (e.g., setting goals). Few works have dealt with the use of optional activities and the relation-ships between these activities and other metrics in VLEs. This paper analyzes the use of optional activities at different levels in a specific case study with 291 students from three courses (physics, chemistry and mathematics) using the Khan Academy platform. The level of use of the different types of optional ac-tivities is analyzed and compared to that of learning activities. In addition, the relationship between the usage of optional activities and different student be-haviors and learning metrics is presented