Enhancing Student Learning with Podcasting, a Newly Emergent Social Technology

The complement between pull and push learning modes is believed to be contributable to enriching students’ learning experiences. Podcasting, a push technology, can be used to push teaching materials to the students’ handheld devices, allowing them to study without any geographical and temporal constraints. The students can then revise the materials according to their own preferences. This explicit push technology together with students’ implicit pull motivation can encourage the students to learn in a more efficient way. As the students have the autonomy to choose their preferred media to access learning materials, it is believed to be able to increase students’ satisfaction in the learning process. We implemented this idea in one of the courses taught in a university in Hong Kong. The encouraging findings confirmed with our belief that podcasting can help students to learn better by increasing their learning satisfaction.

[1]  Wynne W. Chin Partial least squares for IS researchers: an overview and presentation of recent advances using the PLS approach , 2000, ICIS.

[2]  C. Fornell,et al.  Evaluating structural equation models with unobservable variables and measurement error. , 1981 .

[3]  Jiinpo Wu,et al.  The Efficacy Of Online Cooperative Learning Systems , 2006 .

[4]  Christian Wagner,et al.  Weblogging: A study of social computing and its impact on organizations , 2008, Decis. Support Syst..

[5]  Ilze Zigurs,et al.  A Theory of Task/Technology Fit and Group Support Systems Effectiveness , 1998, MIS Q..

[6]  Alan R. Dennis,et al.  Understanding Fit and Appropriation Effects in Group Support Systems via Meta-Analysis , 2001, MIS Q..

[7]  Wynne W. Chin The partial least squares approach for structural equation modeling. , 1998 .

[8]  Dale L. Goodhue,et al.  Development and Measurement Validity of a Task-Technology Fit Instrument for User Evaluations of Inf , 1998 .

[9]  J. Lohmöller Predictive vs. Structural Modeling: PLS vs. ML , 1989 .

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

[11]  Xianggui Qu,et al.  Multivariate Data Analysis , 2007, Technometrics.

[12]  J. Iivari The organizational fit of information systems , 1992, Inf. Syst. J..

[13]  Mihir A. Parikh,et al.  Utilizing Internet technologies to support learning: an empirical analysis , 2002, Int. J. Inf. Manag..

[14]  Doug Schuler,et al.  Social computing , 1994, CACM.

[15]  Izak Benbasat,et al.  The Effect of Multimedia on Perceived Equivocality and Perceived Usefulness of Information Systems , 2000, MIS Q..

[16]  Jonathan T. Copley,et al.  Audio and video podcasts of lectures for campus‐based students: production and evaluation of student use , 2007 .

[17]  J. Livari,et al.  The organizational fit of information systems , 1992 .

[18]  Likoebe M. Maruping,et al.  Managing team interpersonal processes through technology: a task-technology fit perspective. , 2004, The Journal of applied psychology.

[19]  Chris Evans,et al.  The effectiveness of m-learning in the form of podcast revision lectures in higher education , 2008, Comput. Educ..

[20]  F. Bookstein,et al.  Two Structural Equation Models: LISREL and PLS Applied to Consumer Exit-Voice Theory , 1982 .