Introduction
This chapter will explore various dimensions of evaluation in reference to blended learning. Drawing in all that you have learned so far in this guidebook, it will give you a framework not only to evaluate your particular blended learning course or programme but also to weigh the pros and cons of different learning designs, identify key principles and gradually develop your own personal teaching philosophy for blended learning.
Models for Evaluating the Design and Delivery of Blended Learning
Although blended learning is now part of the narrative in education almost everywhere, it can still be a challenge to define and describe the concept. Many who are looking at or already working with blended models are doing so with little support or training. Requirements for engaging processes and quality outcomes are often not obvious to administrators, faculty, instructors or students.
Further, expertise in technology implementation, instructional design, teaching models and learning theory must be developed or accessed. Four general factors must be represented in the design and evaluation of blended learning:
The quality of a blended learning course or programme must be assessed, with appropriate guidelines representing the granular practices and outcomes of blending many different teaching and learning opportunities.
This comprehensive guide is an attempt to help navigate this complex challenge and begin to understand the components of blended learning, its benefits and value, and the required design processes. While blended learning is really nothing more than employing a variety of media and methods to provide a mix of online and face-to-face learning, it can become a very difficult process to select from the range of possible combinations of elements, sequences and pacing’s. Once a blended learning design is in place, formative evaluation (continuous during the course or programme) and summative evaluation (at the conclusion of the course or programme) must be a seminal part of the quality assurance process.
In considering the quality of blended learning, it is helpful to look at the use of online environments and what they offer education. For quality online learning, certain requirements must be present as key parts of any blended environment; these requirements can also be extended to synchronous or in-person activities as the more traditional part of the blend.
Online learning can:
Online opportunities can provide quality education to an expanded audience previously left out of exclusive and often costly, geographically bound, place-based education. Blended learning, as a further development of online learning, should strive to create these same benefits for learners through both its online and in-person, face-to-face components.
With such a range of possible factors for assessing quality and improvement, how then do we evaluate our blended learning courses and programmes? Quality assessment rubrics for blended learning have yet to be well-researched and implemented, and a significant, widely accepted instrument to evaluate blended learning quality is still unavailable. According to Smyth (2017), “the means to evaluate its effectiveness is frequently lacking since there are a relatively limited range of tools and methods that support staff in designing blended learning curricula” (p. 854). Creating such an instrument is a major undertaking; blended learning incorporates and integrates traditional and online delivery methods, making it much more complex than uni modal delivery. This guidebook is one step towards this larger goal, and although evaluation rubrics normally follow curriculum processes, here we offer you advice and templating suggestions for blended learning evaluation.
In our search for rubrics to recommend, we looked for a tool that included “aspects not obvious to instructors or learners, such as instructional design, course development, and the use of technology” (Smythe, 2017, p. 855). Some early tools and rubrics are available and in use, with varying levels of sophistication in measurement and concepts. In other words, opportunities to measure blended learning quality also vary in quality! We recommend reviewing the tools suggested below, looking for others to add to your knowledge base, and then considering developing rubrics and concept maps for your own use.
Blended Course Learnability Evaluation Checklist
The Blended Course Learnability Evaluation Checklist (http://oasis.col.org/handle/11599/2941), developed by the Commonwealth of Learning, can be used to measure the quality of a blended course or as a guide during course development. This tool is divided into six sections, all evaluating the key aspects of a blended course as identified by this guide. This tool can be used as a design template or as an evaluation tool after design and implementation.
Using Community of Inquiry Indicators to Assess Presence in Blended Learning
Earlier in this guide, we reviewed the Community of Inquiry theoretical framework. The framework offers pedagogical guidance for designers, instructors and students interested in collaborative, constructivist learning environments to foster deep learning. The main model includes three presences, as indicated in Table 8.1. Each presence also has sub-elements or characteristics that indicate when a participant is present.
Emotional presence has been suggested as a fourth presence. More research is underway to test the place of emotions in this theoretical framework. However, early indicators are that emotions play an important part in the design and evaluation of blended learning. The preliminary definition of emotional presence is “the outward expression of emotion, affect, and feeling by individuals and among individuals in a community of inquiry, as they relate to and interact with the learning technology, course content, students, and the instructor” (Cleveland-Innes & Campbell, 2012, p.289). this aspect of the learning environment must be considered in person and online, synchronously and asynchronously.
Table 8.1. Evaluation indicators for blended learning in the CoI framework
Learning climate/risk-free expression