Facilitating Deep Learning in a Learning Community

Facilitating Deep Learning in a Learning Community

Hea-Jin Lee (The Ohio State University at Lima, USA) and Eun-ok Baek (California State University, San Bernardino, USA)
Copyright: © 2012 |Pages: 13
DOI: 10.4018/jthi.2012010101
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Abstract

The purpose of this study is to explore how the integration of online discussion into a mathematics methods course affected pre-service teachers’ learning. Students’ transcription of online discussion was analyzed using a mixed methods approach, combining computer-mediated discourse analysis and Chi-square test analysis. The data revealed that the online discussion helped pre-service teachers not only deepen their learning of mathematics methods, but also demonstrated their abilities to teach mathematics in different ways. It also indicated that the depth of their learning depended on the levels of threads and topics of discussion. Deep learning occurs 1) more often in the first level thread than subsequent level threads, and 2) in discussion topics, primarily those related to practice-based issues rather than theory-based topics.
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Introduction

In recent years, online learning has become prevalent in teacher education programs. Research suggests that teachers’ deep learning can be effectively supported in professional environments using online discussion tools (Baek & Barab, 2005; Juan, Steegmann, Huertas, Martinez, & Simosa, 2011; Ryan & Scott, 2008; Yuen & Ma, 2008). When online learning environments are designed to support meaningful interaction between pre-service teachers, deep learning can result through reflection and articulation of belief systems (Dettori, Giannetti, & Persico, 2006; Li, 2005; Schlager & Fusco, 2004).

This provides opportunities for pre-service teachers to both accumulate knowledge and learn what it means to teach, and not only mathematics. Many mathematics teacher education programs incorporate online discussions to help pre-service teachers be actively engaged in deep learning of mathematics (Brendefur & Fryholm, 2000; Breyfogle, 2005; Cady, & Rearden, 2009; Liu, 2008). To make the process of learning to teach mathematics a successful experience, teachers need a foundation for their learning: a deep understanding of mathematics that enables them to reason from basic mathematic principles (NCTM, 2000).

Recent reforms in mathematics education have also encouraged learners to use various forms of communications in order to become engaged in deep learning of mathematics content through reflection (Brendefur & Fryholm, 2000; Breyfogle, 2005). Having content knowledge and being able to reflect one’s own experiences cannot be overemphasized in initial teacher preparation and in-service professional development (Cady & Rearden, 2009; LaBoskey, 1994; Schön, 1987; Shulman, 1987).

The success of an online discussion can be measured by the amount of learning that has taken place or how much deep and surface learning of the topic has been demonstrated in the discussion threads (Chacon, 2005; Cheung & Hew, 2005; Gerbic & Stacey, 2005). While there have been some studies (Henri, 1991; McKenzie & Murphy, 2000) about deep and surface learning in online contexts, Gerbic and Stacey (2005) argue that deep and surface learning have not been substantially examined in a computer mediated learning environment. It is therefore important to be able to gauge whether or not learning has taken place.

In this study, we focused on the influences of asynchronous online discussion to facilitate deep learning of mathematics via reflection. Specifically, this study examined the depth of learning (deep and surface) using analytical lenses proposed by Gerbic and Stacey (2005). Next, this study examined variables (level of discussion threads and nature of discussion topics) that are related to the depth of learning.

The findings of this study will be helpful to teacher educators who are interested in incorporating online discussion to facilitate deep learning which extends classroom discussion. This study will confirm the categories to analyze deep and surface learning.

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