Anastasios Karakostas

Adaptive Collaboration Scripting: A Conceptual Framework and a Design Case Study

Collaboration scripts are didactic scenarios that guide and support groups of learners in collaborative learning. Adaptive collaboration scripting is the idea that collaboration scripts can be adapted during run time in several of their aspects, to provide learning experiences tailored to individual and group characteristics. In order to build systems that support this type of adaptation, one needs to implement adaptation models that consider both the user characteristics (at individual and/or group level) and the script features. Especially for the latter, it is important to distinguish between ldquointrinsicrdquo and ldquoextrinsicrdquo aspects of the script, identifying what aspects should be considered as non-adaptable core script features and what aspects are negotiable and adaptable. Within this context, the scope of this work is twofold: (a) to provide an introductory conceptual framework for adaptive collaboration scripting, and (b) to present a case study on the design of a Web-based system for supporting the adaptive operation of a ldquopyramidrdquo type collaboration script.

Enhancing collaborative learning through dynamic forms of support: the impact of an adaptive domain‐specific support strategy

Research on computer-supported collaborative learning (CSCL) has strongly emphasized the value of providing student support of either fixed (e.g. collaboration scripts) or dynamic form (e.g. adaptive supportive interventions). Currently, however, there is not sufficient evidence corroborating the potential of adaptive support methods to improve domain-knowledge acquisition in collaborative activities. Furthermore, available adaptive CSCL systems are difficult to integrate in everyday instruction because most of them are research prototypes. This study investigates the capacity of an adaptive support strategy [implemented in the open source Learning Activity Management System (LAMS) environment] to further improve learning outcomes in the context of a scripted collaborative activity. Thirty-six students collaborated remotely in dyads on a task structured by a collaboration script. Control group dyads worked without any additional support. Treatment dyads were supported by a domain-specific adaptive intervention in the form of reminding prompts. Treatment students outperformed those in the control group in domain knowledge acquisition. Overall, this study provides evidence that (1) adaptive forms of domain-specific support can substantially improve learning in the context of a scripted collaborative activity; and (2) implementing simple forms of adaptive support is feasible and can be easily implemented by instructors in a freely available collaboration support system (such as LAMS).

Adaptation patterns in systems for scripted collaboration

This work presents a prototype method (DeACS) for identifying useful adaptation patterns to be embedded in systems for adaptive collaboration scripting. Collaboration scripts are didactic scenarios that guide and support the collaborative learning activity while adaptive collaboration scripting is the idea that computer-supported collaboration scripts can be adapted during run time, to provide learning experiences tailored to individual and group characteristics. An adaptation pattern is described as a well-defined adaptation process that can be initiated by the system when specific conditions are identified during script implementation. In order to model the proposed method twelve postgraduate students were engaged in a pyramid-type collaboration script and the analysis of the learning experience provided the basis for identifying a number of possible adaptation patterns. The paper discusses also next steps for advancing the design and evaluation of adaptation patterns in systems for scripted collaboration.

Efficacy and Safety of Crocus sativus L. in Patients with Mild Cognitive Impairment: One Year Single-Blind Randomized, with Parallel Groups, Clinical Trial

There is evidence to suggest the efficacy of Crocus (saffron) in the management of cognitive decline. This study examined the efficacy of Crocus in patients with amnesic and multi domain MCI (aMCImd). The participants included 17 patients on Crocus and 18 on a waiting list, who were examined with a short neuropsychological battery, MRI 3T, while some patients were examined via 256-channel electroencephalogram (HD-EEG) at baseline and after 12 months. The results showed that patients on Crocus had improved Mini-Mental State Examination scores (p = 0.015), while the control group deteriorated. Also, MRI, EEG, and ERP showed improvement in specific domains. This led us to conclude that Crocus is a good choice for management of aMCImd.

A Sensor-Based Framework to Support Clinicians in Dementia Assessment: The Results of a Pilot Study

This paper presents the main mechanisms of a sensor-based framework to support clinical diagnosis of people suffering from Alzheimer disease and dementia. The framework monitors patients at a lab environment while trying to accomplish specific tasks. Different types of sensors are used for monitoring the patients, while a graphical user interface enables the clinicians to access and visualize the results. Sensor data is semantically integrated and analyzed using knowledge-driven interpretation techniques based on Semantic Web technologies. Moreover, this paper presents encouraging preliminary results of a pilot study in which 59 patients (29 Alzheimer disease –AD– and 30 mild cognitive impairment –MCI) participated in a clinical protocol. Their analysis indicated that MCI patients outperformed AD patients in specific tasks of the protocol, verifying the initial clinical assessment.

MentorChat: Introducing a Configurable Conversational Agent as a Tool for Adaptive Online Collaboration Support

Research in the field of computer-supported collaborative learning (CSCL) has systematically indicated that providing adaptive support to collaborating students is an efficient way of improving the outcomes of the collaborative learning activity. In this paper we introduce Mentor Chat, a web-based system that supports collaborative learning by utilizing a Conversational Agent. This agent, which can be easily configured through Mentor Chat authoring environment, aims to intelligently facilitate and trigger the discussion that takes place among partners. To achieve this, Mentor Chat models the domain through a series of key concepts and enables the teacher to define the form of agent intervention when a key concept is traced in students¢ dialogue. We present the system architecture and initial field evaluation data from two studies focusing on end-user acceptance of the system. We also discuss future system improvements and research agenda to explore the impact of Mentor Chat in collaborative learning settings.

Opportunities and Challenges for Adaptive Collaborative Support in Distributed Learning Environments: Evaluating the GLUE! Suite of Tools

Adaptive Collaborative Scripting systems provide learning benefits by adapting leaner scaffolding to the students and their current context. However, their development is still in its infancy and they are not widespread in the Technology Enhanced Learning TEL practice, which often uses VLEs like Moodle and other Web 2.0 tools. In order to assess the feasibility of applying the ACS approach on a larger scale, this paper presents the initial results of a short-term evaluation of the GLUE! suite of tools. The main goal of this specific evaluation process was to identify possible opportunities and ideas on how to design and deploy adaptive Computer- Supported Collaborative Learning (CSCL) activities using widespread VLEs and Web 2.0 tools in order to maximise community acceptance and lower development efforts. The main findings of the evaluation provide incentive to further explore both the impact and the complexity of the design and the deployment of adaptive collaboration scripts.

Introduction to Adaptive Collaboration Scripting

Adaptive collaboration scripting is the idea that computer-supported collaboration scripts can be adapted during run time in several of their aspects, to provide learning experiences tailored to individual and group characteristics. The pedagogical rationale of this idea is to bring together and reap the benefits of two important learning design approaches, namely adaptation of the learning environment and scripted collaborative learning. In this chapter we analyze some of the major pedagogical and technical issues related to the design and development of systems for adaptive collaboration scripting (ACS systems). At pedagogical level, we provide methodological steps on how to build systems for adaptive collaboration scripting, explaining why it is important to distinguish between “intrinsic” and “extrinsic” aspects of the script. At technical level we present a generalized architecture for systems that adaptively support learners during scripted collaboration sessions. The implementation of this conceptual framework is further illustrated by a case study on the design of a web-based system for supporting the adaptive operation of a “pyramid” type collaboration script.

Fade-out and Peer Monitor Techniques in Tools for Scripted Argumentation: Evaluation Results from a Case Study

In this work we present empirical data on the impact of implementing (a) micro-script fade-out and (b) peer monitoring techniques in the context of a web-based argumentation activity in a computer science course. We used the iArgue tool which is a web tool for argumentation incorporating collaboration scripts to structure peer interaction. Additionally, it supports fade-out and peer-monitoring techniques. During the activity students followed the phases of a jigsaw script while micro script support on argumentation faded-out and prompts were activated to remind students to check the validity of their partners’ contributions (peer-monitor). Our results demonstrate the feasibility of incorporating argumentation in computer science courses and provide useful information for improved design of fade-out and peer monitoring techniques to support students’ argumentation.

Towards Integrating Conversational Agents and Learning Analytics in MOOCs

Higher Education Massive Open Online Courses (MOOCs) introduce a way of transcending formal higher education by realizing technology-enhanced formats of learning and instruction and by granting access to an audience way beyond students enrolled in any one Higher Education Institution. However, although MOOCs have been reported as an efficient and important educational tool, there is a number of issues and problems related to their educational impact. More specifically, there is an important number of drop outs during a course, little participation, and lack of students’ motivation and engagement overall. This may be due to one-size-fits-all instructional approaches and very limited commitment to student-student and teacher-student collaboration. This paper introduces the development agenda of a newly started European project called “colMOOC” that aims to enhance the MOOCs experience by integrating collaborative settings based on Conversational Agents and screening methods based on Learning Analytics, to support both students and teachers during a MOOC course. Conversational pedagogical agents guide and support student dialogue using natural language both in individual and collaborative settings. Integrating this type of conversational agents into MOOCs to trigger peer interaction in discussion groups can considerably increase the engagement and the commitment of online students and, consequently, reduce MOOCs dropout rate. Moreover, Learning Analytics techniques can support teachers’ orchestration and students’ learning during MOOCs by evaluating students’ interaction and participation. The research reported in this paper is currently undertaken within the research project colMOOC funded by the European Commission.