Promoting the Use of Online Social Technology as a Case-Based Learning Tool

1. INTRODUCTION An increasing number of educators are considering the use of social media as a pedagogical tool because of its popularity among college students. However, most of these educators are still uncertain as to how to integrate this technology into the management curriculum in order to help students improve their understanding of business cases (Khadijah, Rahman, and MohdNasir, 2011). Online social technology is embedded with four primary technical features: sharing, grouping, conversation, and relationships (Hu and Gollin, 2010). These features correspond with four essential elements of case-based learning, which are sharing knowledge, learning in groups, constantly exchanging information with other group members, and building constructive relationships (Chen, Chen, and Kinshuk, 2009). If used properly, social technology could be an effective tool to help students acquire skills in analytical and diagnostic thinking, develop strong persuasive skills, and make decisions under conditions of uncertainty (Hackney, McMaster, and Harris, 2003; Lee et al., 2009). Educators can also benefit by using social technology to reach more case-based learners. In order to realize the potential of using social technology, educators and administrators need to first promote its use for case-based learning. In the meantime, they need to assess the efficacy of this technology in case-based learning applications. The primary purposes of this preliminary study are to (1) understand users' perceived usefulness of social technology for case-based learning and (2) assess the potential impact of it on users' case-based learning performance. Goodhue and Thompson (1995) suggest that information technology is more likely to have a positive impact on users' performance and usage if the capabilities of the information technology match the tasks that the users must carry out. Therefore, this study will adopt the task-technology fit perspective to examine how these four technical features, sharing, grouping, conversation, and relationships, would contribute to the use of social technology for case-based learning. The aim of this study is to determine if online social technology is a good fit as an online learning technology for business students to acquire case-based learning skills and knowledge. Section 2 will first examine literature related to these four technical features or constructs, and pose specific research questions on their potential influence on the use of social technology for case-based learning. Section 3 will discuss the experimental setting, data collection procedure, and data analysis methods. Section 4 will present the results from the data analysis to answer the proposed research questions. The remaining sections will present study limitations and proposed future research, as well as scholarly and practical implications. 2. LITERATURE REVIEW 2.1 Social Capital and Case-Based Learning Social capital is the actual and virtual resources accumulated via the social networks or relationships among people (Coleman, 1988). The more social capital that is available in an online community, the more the members will contribute to it. Because social capital is a cause and effect phenomena (Williams, 2006), the increase of it relies on the mutual support among the members to produce positive social outcomes (e.g. trust, shared information, self-esteem) (Adler and Kwon, 2002). Although social capital underpins the success of online social networks, developing it effectively remains a challenge for many online communities. Social capital cultivation is particularly important for the success of case-based learning, an important element of management education. In a face-to-face environment, students have plenty of opportunities to interact with each other, with their team members, guest speakers, and their instructor. Before each class discussion, students need to study the facts related to the particular business case, and define the problems faced by the different/various stakeholders involved in it. …

[1]  Naresh K. Malhotra,et al.  Marketing Research: An Applied Orientation , 1993 .

[2]  J. Coleman,et al.  Social Capital in the Creation of Human Capital , 1988, American Journal of Sociology.

[3]  J. W. Asher,et al.  Educational research and evaluation methods , 1976 .

[4]  Nian-Shing Chen,et al.  Examining the Factors Influencing Participants' Knowledge Sharing Behavior in Virtual Learning Communities , 2009, J. Educ. Technol. Soc..

[5]  P. Adler,et al.  Social Capital: Prospects for a New Concept , 2002 .

[6]  Patient Rambe,et al.  Journal of Information Technology Education Exploring the Impacts of Social Networking Sites on Academic Relations in the University , 2022 .

[7]  Ray Hackney,et al.  Using Cases as a Teaching Tool in IS Education , 2003, J. Inf. Syst. Educ..

[8]  A. Bandura Self-efficacy: toward a unifying theory of behavioral change. , 1977, Psychology Review.

[9]  Garry Falloon,et al.  Exploring the Virtual Classroom : What Students Need to Know ( and Teachers Should Consider ) , 2011 .

[10]  Lori B. Holcomb,et al.  The Use of Alternative Social Networking Sites in Higher Educational Settings: A Case Study of the E-Learning Benefits of Ning in Education , 2010 .

[11]  Politécnica de Valencia,et al.  Xedu, a Proposal of Learning Management System Implementation , 2004 .

[12]  Curtis J. Bonk,et al.  A Review of Case-based Learning Practices in an Online MBA Program: A Program-level Case Study , 2009, J. Educ. Technol. Soc..

[13]  Curtis J. Bonk,et al.  The Importance of Interaction in Web-Based Education: A Program-Level Case Study of Online MBA Courses , 2005 .

[14]  E. Thorndike,et al.  The influence of improvement in one mental function upon the efficiency of other functions. II. The estimation of magnitudes. , 1901 .

[15]  WenChieh Wu,et al.  The Effectiveness of e-Learning for Blended Courses in Colleges: A Multi-level Empirical Study , 2010, Int. J. Electron. Bus. Manag..

[16]  Richard V. McCarthy,et al.  Analyzing the Factors That Affect Information Systems Use: A Task-Technology Fit Meta-Analysis , 2009, J. Comput. Inf. Syst..

[17]  Bo Hu,et al.  Supporting Case-Based Learning Through a Collaborative Authoring System , 2010 .

[18]  Khadijah Abdul Rahman,et al.  The Effectiveness of Learning Management System (LMS) Case Study at Open University Malaysia (OUM), Kota Bharu Campus , 2010 .

[19]  Chulmo Koo,et al.  Examination of how social aspects moderate the relationship between task characteristics and usage of social communication technologies (SCTs) in organizations , 2011, Int. J. Inf. Manag..

[20]  Michael DeSchryver,et al.  Moodle vs. Facebook: Does using Facebook for Discussions in an Online Course Enhance Perceived Social Presence and Student Interaction? , 2009 .

[21]  Dale Goodhue,et al.  Task-Technology Fit and Individual Performance , 1995, MIS Q..

[22]  Christian Voigt,et al.  The affective domain and social networking : definitorial issues and misleading assumptions , 2010 .

[23]  Stylianos Hatzipanagos,et al.  Technologies and Practices for Constructing Knowledge in Online Environments , 2010 .

[24]  Ilze Zigurs,et al.  A test of task-technology fit theory for group support systems , 1999, DATB.

[25]  Dmitri Williams,et al.  On and Off the 'Net: Scales for Social Capital in an Online Era , 2006, J. Comput. Mediat. Commun..