“Conceptual Reverse Engineering” of Online Learning Objects and Sequences for Practical Applications

Introduction

A common analytical process in instructional design involves the conducting of environmental scans of online learning objects and sequences (and raw digital files) available online related to a particular subject or topic. “Conceptual reverse engineering” refers to the analysis of finalized digital learning objects and sequences and backwards inducing what went into the design and development of those contents. While “reverse engineering” generally refers to reproducing someone else’s product after examining its composition and construction, this is not about a full re-making but rather examining others’ learning objects and sequences in depth to understand how it was made—not to copy it…but to glean understandings. The “backwards induction” refers to starting with an object in its end state and analyzing and inferring how it may have come into being. This analysis involves analyzing a range of relevant features, and the information may be applied to various practical understandings and decision-making:

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  Understanding the state of the art.

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  Informing competing designs methods.

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  Informing the selection of technologies.

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  Enabling the budgeting of design and development work.

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  Informing decisions on whether or not to adopt third-party learning objects, and others.

This approach is conceptual in the sense that these are run initially as “thought experiments” and inferences about the designs. The next logical step in is to test the theorized designs by testing the learning object and its constituent parts; actually disaggregating the learning objects and sequences; reaching out to the original design and development teams; and reviewing raw files from the design and development. An assumed design is only that, and depending on who is conducting the conceptual reverse engineering and how much information is available, such a work can be fairly far off of accurate. That said, “conceptual” does not mean that the information is impractical or non-applied; as noted, this information may be applied to awareness, decision-making, budgeting, and other practical applications. The backwards induction analysis process of conceptual reverse engineering has not been systematized nor documented. Its (in)validity and strengths/weaknesses have not been assessed. This early work strives to lay the groundwork by describing this process and offering some analysis of it. The two hypotheses of this work read:

• Hypothesis 1: It is possible to conceptually reverse-engineer online learning objects and online learning sequences to make some informative inferences about their design and development.

• Hypothesis 2: The method for conceptual reverse-engineering online learning objects and online learning sequences may be somewhat systematized and described.

It is hoped that this may inform the analytical work and decision-making of others and that others may build on this work.

Review Of The Literature

The term “learning object” was first used in 1994 by H. Wayne Hodgins when he named a working group for the Computer Education Management Association (CEdMA) “Learning Architectures, APIs and Learning Objects” (Polsani, 2003, p. 1). Learning objects may be digital, non-digital, or a combination of both, and a key feature is that they can be “used, re-used or referenced during technology supported learning” (Wiley, June 2000, p. 3). Online, there is a lot of duplicated learning information (Oliver, 2001), which suggests excessive “reinventing the wheel” and wasted design and development resources. The relative size of a learning object is important to its uptake, with the convention wisdom being that the smaller and more atomistic and basic an object is, the easier it is to use across a range of contexts; the larger the object (think modules, think courses), the less inheritable into existing learning sequences. Learning objects are conceptualized as fulfilling a list of so-called “ilities”: