No abstract

No abstract

The popularity of online programs that educational institutions offer is continuously increasing at varying degrees, with the major demand coming from adult learners who have no opportunity to access traditional education. These adult learners have to be sufficiently ready and competent for online learning, and have their own varied expectations from the online learning process. Hence, this mixed method study is conducted to explore the participants’ readiness and expectations at the beginning and their satisfaction levels at the end of an online learning experience. An e-readiness scale and an e-satisfaction scale was administered as quantitative measures, with open-ended questions gathering qualitative data. Participants of the research were registered to different e-learning programs at Ankara University Distance Education Center, Turkey, during the 2013-2014 academic year. Analysis of both quantitative and qualitative data revealed facts about online learners, which should prove useful to both e-instructors and e-program administrators.

No abstract

This study aims at analyzing possible predictors of technology acceptance model based on qualitative review of relative articles. Thus, within the scope of this study articles which had based their theoretical framework on Technology Acceptance Model (TAM) were screened. For this reason, fifty papers, which were published in thirty-two journals and nine conferences between the years 1999 and 2010, were reviewed. In terms of the articles reviewed, search results revealed that most of the research studies were in the fields of education and business. These papers were examined with three main objectives in mind: (1) to investigate TAM variables that were found effective and ineffective from a critical point of view; (2) to highlight the top use of the effective variables; (3) to compose the study fields of TAM. These papers were analyzed through content analysis by an inductive approach. In the first stage coding was carried out according to previously identified concepts (scanning, selection criteria) and themes that were emerged in this context. Then the data were organized and grouped according to themes and presented by means of making numerical transformation in appropriate cases. Finally, the obtained findings were interpreted. The results showed that the main variables of "Technology Acceptance Model" were remained as the most effective ones though numerous attempts have been made to add other variables to existing ones.