Engaging online learners: The impact of Web-based learning technology on college student engagement

Center for Postsecondary Research, Indiana University Bloomington, USA
Computers & Education (Impact Factor: 2.56). 05/2010; 54(4):1222-1232. DOI: 10.1016/j.compedu.2009.11.008
Source: DBLP


Widespread use of the Web and other Internet technologies in postsecondary education has exploded in the last 15 years. Using a set of items developed by the National Survey of Student Engagement (NSSE), the researchers utilized the hierarchical linear model (HLM) and multiple regressions to investigate the impact of Web-based learning technology on student engagement and self-reported learning outcomes in face-to-face and online learning environments. The results show a general positive relationship between the use the learning technology and student engagement and learning outcomes. We also discuss the possible impact on minority and part-time students as they are more likely to enroll in online courses.

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Available from: Pu-Shih Daniel Chen, Aug 08, 2015
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    • "Emergent research indicates that Social Media applications have made exponential and potent in-road in higher education over the last 5 years (Bennett et al., 2012; Brown, 2012; Carroll et al., 2011; Chen et al., 2010; Everson et al., 2013; Friedman & Friedman, 2013; Huang et al., 2011; Hung & Yuen, 2010; Junco, 2012; Mazman & Usluel, 2010; Piotrowski 2015; Prates et al., 2013; Sim & Hew, 2010; Tess, 2013; Voorn & Kommers, 2013; Wang et al., 2012), including applications in graduate-level coursework (e.g., Meyer, 2010). However, the impetus for the integration of Web 2.0 communicative technologies in education has been predominantly robust and without criticism. "

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    • "Bunlardan, Holley ve Dobson (2008) ile Chen, Lambert ve Guidry (2010)'nin çalışmalarının bu çalışmadan farklılaşan yönlerinden biri örneklemin büyüklüğünün geniş tutulması olarak gösterilebilir. Bununla birlikte belirtilen çalışmaların (Holley ve Dobson, 2008; Chen, Lambert ve Guidry, 2010; Sarıtepeci ve Yıldız, 2014) örneklemini oluşturan katılımcıların lise ya da üniversite düzeyinde olması da önemli bir farklılık olarak görülebilir. Bu çalışmanın sonuçlarıyla belirtilen çalışmalar arasındaki bu farklılığın başka bir sebebi de bu çalışmanın sınırlılıklarıyla açıklanabilir. "

    Eğitim ve Bilim 02/2015; 40(177). DOI:10.15390/EB.2015.2592 · 0.32 Impact Factor
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    • "In fact, collaborative learning comprises students' interaction and network connections with their peers and with the curriculum. To this end, according to Chen et al. (2010), student staking online courses spend most of their time making use of online tools and social media to supplement their learning tools compared to their counterparts who learn through face-to-face instruction. Hence, it is logical to conclude that active engagement, collective learning and mapping out of virtual relationships via social media open up opportunities for maximized learning as students are motivated to develop a network of connections with sources extending outside of their classrooms (Fewkes and McCabe, 2012; Yu et al., 2010). "
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    ABSTRACT: As social networks continue to proliferate, the question arises as to how to attract students and researchers to different online sites. In this regard, the present study focused on the interactivity of social networks and their role in satisfying students. Accordingly, this study proposed a model comprising of factors that assist in answering the study questions. A developed questionnaire was then distributed to 132 students and users' of social media websites that obtains relevant information regarding technology acceptance, interactivity and satisfaction of students. The findings suggested that both Technology Acceptance Model (TAM) related factors as well as interactivity affect the satisfaction and academic performance of students.
    Research Journal of Applied Sciences, Engineering and Technology 01/2015; 9(12):1132-1142.
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