A computer-mediated support system for project-based learning

Laffey, James M.; Tupper, Thomas; Wedman, John; Musser, Dale

doi:10.1007/bf02299830

Cited by 96 publications

(51 citation statements)

References 11 publications

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“…Collaboration can be characterized by three important elements: independence [14], interdependence [15] and synthesis of information [16] . The three elements work together for effective online collaborative learning.…”

Section: B Analyzing Collaborationmentioning

confidence: 99%

Using Machine Learning Techniques to Support Group Formation in an Online Collaborative Learning Environment

Maina¹,

Oboko²,

Waiganjo³

2017

IJISA

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Abstract-The current Learning Management Systems used in e-learning lack intelligent mechanisms which can be used by an instructor to group learners during an online group task based on the learners" collaboration competence level. In this paper, we discuss a novel approach for grouping students in an online learning group task based on individual learners" collaboration competence level. We demonstrate how it can be applied in a Learning Management System such as Moodle using forum data. To create the collaboration competence levels, two machine learning algorithms for clustering namely Skmeans and Expectation Maximization (EM) were applied to cluster data and generate clusters based on learner"s collaboration competence. We develop an intelligent grouping algorithm which utilizes these machine learning generated clusters to form heterogeneous groups. These groups are automatically made available to the instructor who can proceed to assign them to group tasks. This approach has the advantage of dynamically changing the group membership based on learners" collaboration competence level.

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Section: B Analyzing Collaborationmentioning

confidence: 99%

Using Machine Learning Techniques to Support Group Formation in an Online Collaborative Learning Environment

Maina¹,

Oboko²,

Waiganjo³

2017

IJISA

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“…Problem driven refers to emphasize the meaning of the problem, students find and select problem in real life; inquiry is defined middle school students to make assumptions in PBS learning activities, and to discuss the different hypotheses, design of plan or experimental scheme, information collection, analysis of data, forming a conclusion; works guide the students to complete a series of learning outcomes in explore; cooperation refers to each discussion among the students, teachers and members in the learning community; technology refers to the use of computer technology to obtain data and information [9,10].…”

Section: Pbs Teaching Patternmentioning

confidence: 99%

Scientific Inquiry of the Project Cooperation PBS Teaching Mode under MATLAB Fitting

Zhao¹,

Mi²

2013

Proceedings of the 2nd International Conference on Management Science and Industrial Engineering (MSIE 2013)

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Abstract. Based on project science teaching mode, to expand students' thinking and develop the research ability of the students, it need to team cooperation as dominant and scientific inquiry as the core, which are widely research and application in the United States science education and middle school classrooms. In view of the present situation of China education modernization, to briefly expound PBS teaching model, and then to carry out science status quo of PBS teaching mode, finally to carry out PBS teaching model empirical analysis in the MATLAB fitting, which can obtain the PBS that can deepen the students for the understanding of science, to effectively promote the effectiveness of teaching.

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“…Efforts to include better preparations have begun for pre-service teachers within methods coursework and during student teaching, but the foundation needs to be laid earlier in the education program. Laffey and Musser (1998) suggested that teacher education programs need to incorporate technology into the curriculum in order to motivate teacher candidates to creatively utilize technology. Pre-service teachers who experience modeling of relevant usage of technology will be more likely to implement this approach within their own classrooms.…”

Section: Relevance and Significancementioning

confidence: 99%

“…Theorists suggest that learning is more effective when students are able to discuss their ideas, experiences and perceptions with peers (Jonassen & Kwon, 2001;Kanuka & Anderson, 1998). Some researchers have indicated that the flexibility and technological support for such interactions available in computermediated environments point to collaborative learning strategies as a promising means to implement new technology (Laffey, Tupper, Musser, & Wedman, 1998;Pena-Shaff & Nicholls, 2004;Strijbos, Martens, & Jochems, 2004;Oliver & Omari, 2001). Furthermore, theorists have indicated that CMC could have greater effects than other modes of interaction on learning in problem-solving, case study, and other higher-order learning situations (Adelskold, Alklett, Axelsson, & Blomgren, 1999;Johnston, 1996;Jonassen, Prevish, Christy, & Stavulaki, 1999).…”

Section: Introductionmentioning

confidence: 99%

“…According to Hara (2002) and Murphy and Collins (as cited in Uribe, Klein, & Sullivan, 2003), research on synchronous CMC has been limited to surveys of students, investigations of the recreational use of online chat systems, and the use of these systems for instructional purposes has been explored only through case studies. Furthermore, among the studies that have examined achievement in the online environment, many consider only one collaborative condition rather than make a comparison of online to face-to-face situations (Berge, 1999;Brewer, 2004;Davies & Graff, 2005;Gunawardena & McIsaac, 2004;Hoskins & van Hooff, 2005;Laffey et al, 1998). Unless comparisons are made, it is difficult to determine the effect of computer-mediated collaboration (CMC) in virtual environments.…”

Section: Introductionmentioning

confidence: 99%

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Tool use in open learning environments: In search of learner-related determinants

Clarebout

Elen

2008

Learning Environ Res

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IntroductionBeliefs about teaching and learning play an important role in transforming classrooms through the use of technology (Ertmer, 1999(Ertmer, , 2005. Additionally, attitudes toward technology can influence teachers' technology uses (Myers & Halpin, 2002;Yildirim, 2000). In order to prepare preservice teachers to use technology effectively, it is necessary to examine their beliefs about learning and teaching and their attitudes toward technology. Teacher educators must act as role models for preservice teachers and prepare them to use technology in their future professional practices. In this paper we report the results of a study that examined teacher educators' beliefs and technology uses in relation to preservice teachers' beliefs and technology attitudes. Ertmer (1999) described two types of barriers to technology integration: first-order barriers and secondorder barriers. First-order barriers are extrinsic to teachers and include lack of access to hardware and software, time, and necessary support. Second-order barriers are intrinsic to teachers and include teachers' belief systems about teaching and learning, as well as their familiar teaching practices, which can affect meaningful technology integration. Since second-order barriers are more ingrained and personal than first-order barriers, they may be harder to overcome. Current literature Niederhauser & Stoddart, 2001; Norm, Grabinger & Duffield, 1999) indicated that teachers who had more constructivist or student-centered beliefs tended to use technology and engage the students in more technology-supported student-centered learning activities, while those who had more traditional or teacher-centered beliefs tended to use less technology and had students use technology to reinforce skills.Some researchers (Cifuentes, 1997;Daniel, 1996; Friel & Carboni, 2000; Hart, 2002) suggested that participation in teacher education programs could influence preservice teachers' beliefs. In teacher education courses, teacher educators create learning environments through specific teaching strategies that allow preservice teachers to experience models of teaching and learning that they might use in their future teaching. Supporting the strategies that teacher educators employ are their underlying beliefs about teaching and learning (Pajares, 1992). Since we may be able to predict teacher educators' teaching practices from their beliefs, and their practices are likely to influence preservice teachers' beliefs, it may be possible to predict preservice teachers' beliefs from teacher educators' beliefs. Thus, one of the research interests in this study was the relationship between teacher educators' beliefs and preservice teachers' beliefs.Besides beliefs, attitudes are thought to serve as predictors of behaviors (Richardson, 2003). Applied to technology use, attitudes toward technology are expected to predict one's uses of technology. According to Aiken (1980), attitudes can be "learned directly by observing the activities of people who are perceived as signific...

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A computer-mediated support system for project-based learning

Abstract: Project-based learning places demands on learners and instructors that challenge the tra-

Cited by 96 publications

References 11 publications

Using Machine Learning Techniques to Support Group Formation in an Online Collaborative Learning Environment

Using Machine Learning Techniques to Support Group Formation in an Online Collaborative Learning Environment

Scientific Inquiry of the Project Cooperation PBS Teaching Mode under MATLAB Fitting

Tool use in open learning environments: In search of learner-related determinants

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