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... For example, in our studies we plan to evaluate the development of social skills among learners as a result of human-human interaction by conducting pre and post assessment of learners' attitude toward collaborative learning and companion learners. Collecting and evaluating data regarding the collaborative learning activity can also be done through analysis of video recordings of the collaborative learning session [54] using analysis methods such as Decision Function Coding Scheme (DFCS) [55,56]. However, these methods often require transcription of dialogues, manual coding, interpretation and inter-rater agreement and are thus open to error and very costly in time and money. ...
Designing a virtual agent architecture that comprises collaboration between the agents and human users remains a challenging issue due to differences in beliefs, ways of reasoning and the abilities used to achieve the common goal. Allowing the agent and human to communicate verbally and non-verbally while achieving the collaborative task, further increases the difficulty of the challenge. In this paper, we present an overview of existing research involving collaborative agents in virtual environments and extend our Multi-Agent Collaborative VIrtuaL Learning Environment (MACVILLE) agent architecture to handle two-way human-agent collaboration. A scenario is provided.
... Qualitative observations of the videos were used to assess whether most of groups' speech was on-task (an average of more than the 89% in each group). Each utterance in a sample of each session (more than the half of each session) was coded using a modified coding scheme for Collaborative Decision Making (Kennedy-Clark, et al, 2011). Off-task speech included all the utterances about anything other than the subject material, management of the group processes or the interaction with the application. ...
During collaborative student work, teachers aim to support groups effectively and ensure that each group member can contribute at some level. Analysing the final product of group work does not reveal individual contributions or the collaborative process. This research investigates indicators of collaborative learning, captured by a novel tabletop environment, which can provide real-time information about the ongoing collaborative work. This can enable teachers to direct their attention more effectively. This paper reports findings from a case study on collaborative concept mapping. Five triads of university students engaged in a collaborative activity on the topic of human nutrition. The variables, level of participation, symmetry of participation, similarity of previous knowledge, knowledge contribution, transactivity, interaction and knowledge creation, were used to describe the collaborative process. Results offer promise for transforming this collaboration data to give informative feedback to teachers and support collaborative learning.
... The DFCS was selected as it includes problem definition, orientation and solution development. In other work (Kennedy-Clark, Thompson, & Richards, 2011) a modified version of the scheme was adopted, based on the availability of data that showed implementation of decisions, and we have included this additional code in our analysis. ...
Debate in the field of event-based analysis of collaborative process data has focused on how best to account for the temporal nature of processes. We reanalyzed data from an online learning environment that included multiple tool use (chat and wiki) in synchronous and asynchronous collaborative settings. In this paper we modeled decision-making, and used time to identify four patterns of tool use to make decisions: single chat, multiple chat, chat/s and follow-up wiki, and integrated. Each pattern of tool use was associated with a unique process model, which indicated the affordances of each tool for that particular activity. The examination of the integrated use of tools, and the integrated decision-making process in a collaborative online setting has implications for designers, instructors and researchers.
Recently, there have been calls to undertake deeper analyses of learner interactions in collaborative computer-supported environments, analyses that move beyond code and count, in order to understand collaboration from multiple viewpoints. In this chapter, two analytical approaches are presented, analyzing and interpreting the same conversational data from learners sharing a computer to solve a virtual inquiry. It is proposed that through the combined use of group function analysis and discourse analysis perspectives, a deeper understanding of how learners interacted on both macro and micro levels can be gained. The patterns of successful and non-successful problem solving are established and, from this, factors that may contribute to goal attainment or non-attainment are outlined.
3D immersive virtual worlds, such as Second Life, have been the focus of substantial
attention from tertiary educators in recent years and the potential for the use of
such environments in learning and teaching contexts has been a frequent topic
of discussion by commentators on higher education futures. However, despite
anecdotal evidence of an increase in usage of such environments for learning and
teaching in Australian and New Zealand higher education, there have been no
published studies reporting on the breadth of use and the nature of the experience
of adopters of such environments across the sector.
This report draws on data from a review and environmental analysis of the use of 3D
immersive virtual worlds in higher education in Australia and New Zealand carried
out by researchers from Charles Sturt University (CSU), the University of New England
(UNE) and the University of Southern Queensland (USQ) from 2010 to 2012. The
study sought to identify and examine existing applications of 3D immersive virtual
worlds by educators throughout the two countries, with the aim of developing an
understanding of how the technology is being used for learning and teaching across
institutions and disciplines and the relevant experiences of academics, educational
designers and Information Technology (IT) support staff.
The study has been carried out under the auspices of the Distance Education Hub
(DEHub at http://www.dehub.edu.au), a federally funded research consortium
based at UNE that involves UNE, CSU, USQ and Central Queensland University in
Australia and Massey University in New Zealand. The study set out to provide the
higher education community with exemplars, guidelines and recommendations to
encourage the successful uptake, implementation and use of 3D immersive virtual
worlds.
The scoping study consisted of three phases of data collection:
1. Literature searches and searches of institutional web sites leading to
the establishment of a database of 179 higher education staff (135 in
Australia and 44 in New Zealand) with an interest or involvement in using
3D immersive virtual worlds for learning and teaching;
2. An online questionnaire completed by 117 respondents, including 82 from
Australia and 35 from New Zealand, to obtain information about the ways in
which 3D immersive virtual worlds were used and about the perspectives of
the teaching staff involved;
3. Interviews to gather more detailed information and perspectives from
13 academic staff who had implemented virtual worlds in their teaching,
from six educational design staff and from five Information Technology (IT)
support staff.
The 62 respondents who indicated they had already used 3D immersive virtual worlds
in their teaching reported on a total of 125 individual subjects in which they had used
the technology, including 201 individual subject offerings. Details were provided
about the use of virtual worlds in 100 subjects. Of these, the majority used Second Life
(78.0%) as the virtual worlds platform, followed by Active Worlds (5.0%) and OpenSim
(4.0%). Within these 100 subjects, the virtual world-based tasks were compulsory
and assessed in 41% of subjects, compulsory but not assessed in 16% and neither
compulsory nor assessed in 43%.
There was a fairly even distribution of subjects using virtual worlds across disciplines,
although the science discipline was somewhat underrepresented. Specifically, 29%
were in the Arts and Humanities, 21% in Education, 18% in Information Technology,
10% in Legal and Business Studies, 9% in Health, 4% in Science and 9% in other
discipline areas. Respondents provided 53 detailed descriptions of the way in which
virtual worlds were used in their teaching, and from these descriptions ten categories
of learning design were identified, with a number of subjects fitting into more than
one category. The most commonly used virtual world supported learning design was
role-play (43% of subjects), followed by learning designs centred on communication
(40%), learning designs focussing on instruction or presentation (23%) and learning
designs focussing on place exploration and building/scripting (each 17%).
Fifty-five respondents provided more detailed information about a specific virtual world
implementation and, of these, 55% indicated that the virtual world, island or space
was developed specifically for the purpose of the subject they taught. Twenty-two per
cent of these 55 respondents indicated that an important aspect of the learning task
was familiarisation with Second Life and, consequently, these respondents indicated
that students were required to explore the environment as a whole, rather than using
a space developed for a specific pedagogical purpose. Of these 55 respondents, 55%
indicated that they had drawn on the support of non academic staff within their
institutions, such as information technology or educational design support staff. Fiftyfive
per cent also indicated that they had drawn upon dedicated funding to support
the implementation, with this funding coming from a variety of internal and external
sources.
Interview participants described a number of different virtual spaces that had been
developed to meet the specific needs of their particular learning context, including a virtual hospital emergency department, a virtual classroom and a simulated street with
retail outlets allowing students to undertake a business role-play. Others described
the development of spaces designed for various types of online teaching including
amphitheatres, boardrooms and informal student meeting spaces. Some of the spaces
developed consisted largely of static building and furniture, while others incorporated
dynamic features controlled by complex scripts; for example, one participant described
a virtual environment containing business outlets controlled by a complex back-end
economic simulation. Other spaces relied on user interface enhancement allowing
avatar control beyond that provided by default within the viewer software.
With respect to evaluation, little systematic evaluation was described in the interviews,
with participants mainly describing informal feedback mechanisms and some types of
formal but not systematic evaluation. Most commonly, participants described informal
student feedback or informal observation of student activity as the main evaluation
mechanisms. Formal evaluation procedures predominately included student subject
evaluation forms that were included as part of a university reporting system. Of those
that did mention systematic evaluation, most referred to research projects associated
with the virtual world implementation.
Respondents to the questionnaire mentioned a number of problems they had
encountered in their attempts to integrate virtual world activities into their teaching
and these problems were grouped into the following categories: technology, support,
funding and time, usability and familiarity, equity and ethics, inherent limitations of
virtual worlds, acceptance of virtual worlds, and management and planning. Interview
participants also provided more detailed descriptions of many of the problems
identified and a number of recommendations for others emerged from both the
questionnaire responses and interviews.
Other perspectives emerging from interviews included identification of a lack of
specific funding for, and an absence of, institutional policies relating to virtual
worlds, an acknowledgement of the need for substantial time commitment by staff
considering the adoption of virtual worlds and noting of the value of working with
others through informal and formal networks. Additionally, academic staff members
interviewed highlighted the increased engagement of students that had occurred
through the introduction of virtual worlds based tasks and the fact that the process
of introducing virtual worlds into their teaching had led to new reflections on their
teaching practice.
Based on the analysis of data collected during this study, along with ongoing reviews
of the emerging literature, a series of recommendations have been derived. These have
been grouped into recommendations relating to institutional policy, recommendations
directed at teaching staff considering the adoption of virtual worlds into their teaching
and recommendations relating to research.
Recently, there have been calls to undertake deeper analyses of learner interactions in collaborative computer-supported environments, analyses that move beyond code and count, in order to understand collaboration from multiple viewpoints. In this chapter, two analytical approaches are presented, analyzing and interpreting the same conversational data from learners sharing a computer to solve a virtual inquiry. It is proposed that through the combined use of group function analysis and discourse analysis perspectives, a deeper understanding of how learners interacted on both macro and micro levels can be gained. The patterns of successful and non-successful problem solving are established and, from this, factors that may contribute to goal attainment or non-attainment are outlined.
