Designing Asynchronous Message Board Assignments for Deep Learning Discourse: A Longitudinal Heuristic Case

Designing Asynchronous Message Board Assignments for Deep Learning Discourse: A Longitudinal Heuristic Case

Shalin Hai-Jew
Copyright: © 2012 |Pages: 22
DOI: 10.4018/978-1-61350-071-2.ch009
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Abstract

Asynchronous message boards provide a critical space for university students to learn collaboration, support each other, and develop critical thinking skills in freshman and sophomore composition and research writing classes. How asynchronous message board assignments—icebreakers, discussion questions, summaries, reading analyses, lead-up assignments (research topic proposals, source evaluations, outlines, and drafts), and cumulative projects—all work towards building reflective online conversations and deep learning. This chapter addresses the evolving strategies that have been used in the deployment of publicly viewable assignments used on asynchronous message boards for freshman and sophomore writing classes since 1997 through the consortium WashingtonOnline (WAOL), which consists of 32 community colleges in Washington State.
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Introduction

The information-based economy assumes a level of information sophistication and literacy to function in a complex global space. This literacy often requires many years of work to acquire and apply. At the university level, freshman and sophomore students begin to explore information in more depth in foundational composition and research writing courses; they look at where information comes from, how it is captured and packaged (in genres, in writing, and in print and electronic forms), how to vet information for credibility, and how to participate in that informational universe by honing their own self-expression, voices, and writing skills. Deep learning in this context involves multiple dimensions.

Deep Learning about Information

Deep learning differs based on the particular disciplinary field. Traditionally, deep learning involves plenty of analyses, sustained and critical discussions, and hands-on applied experiences (including simulations). Deep learning implies transferability of the skillset and knowledge to different learning contexts; it also suggests longitudinal (life-changing) learning.

The Self in Relation to the Information Universe

It is said that while writing is very personal on one level, it has to have social value to make it into publication. It has to offer something of benefit to others, whether that is knowledge or insight or even a sense of aesthetic appreciation. One important deep learning aspect involves knowledge of the information that one has and how one has come by this information and the standards that one applies in vetting what they believe. A critical and difficult lesson for younger students is differentiating between experienced versus inherited information. Many young learners confuse what they have heard from others or seen on the Internet or television (mediated experiences) with their own experiences; they will fall into easy parroting of others’ ideas without a sense of their own lack of expertise in a particular area. Mastering the sense of one’s relationship in the information universe to the larger world involves metacognition (awareness of one’s thinking and learning) and an honest assessment of one’s own skill sets and potential for contributing to the larger world of applicable information. They need to understand discourse as part of a broad range of information exchange and an ongoing social activity; they need to explore the various informational artifacts in the real world—in terms of articles on digital repositories or libraries; scripts; short stories; essays; poems; plays; movies, and multimedia files. They need to synthesize information across various streams and create semi-coherent understandings of a range of topics.

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