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Pedersen, S. (2004). Designing and researching enhancements for online learning: A commentary on Veal, Brantley, and Zulli. Contemporary Issues in Technology and Teacher Education [Online serial], 4(2). Available: http://www.citejournal.org/vol4/iss2/science/article1.cfm
Designing and Researching Enhancements for Online Learning: A Commentary on Veal, Brantley, and Zulli
Susan Pedersen
Texas A&M University
| This commentary on the recent article, "Developing
an Online Geology Course for Preservice and Inservice Teachers: Enhancements
for Online Learning" by Veal, Brantley, and Zulli (2004) examines two
issues related to the design of online courses. First, the concept of affordances
is used to compare face-to-face and online classes for insights into which
instructional strategies are likely to be useful in both settings and which
are not. Second, design-based research, the methodology employed by Veal
et al. in their study, is considered for its potential to guide the investigation
of innovations in online classes. |
As a faculty member teaching graduate classes online, I read Veal, Brantley,
and Zulli’s (2004) recent article, “Developing an Online Geology
Course for Preservice and Inservice Teachers: Enhancements for Online Learning,”
with great interest. In the rush to capitalize on the emerging potentials of
new technologies and meet the needs of a new audience – the distance student
– instructors often must design their courses in the absence of knowledge
about effective techniques for distance education. Information about the challenges
faced by other educators and the strategies they used to enhance learning successfully
within this new medium is, therefore, needed. Veal et al. described a two-phase
study in which they used the literature on successful practices in face-to-face
classes to identify and then implement 10 enhancements to an online course.
They examined the impact of this online course on teachers’ content knowledge,
then investigated teachers’ perceptions of the effectiveness of these
enhancements to their own learning and their potential usefulness for their
future teaching. There is a strong need for such research. Important differences
exist between online and face-to-face classes in terms of the types of instructional
strategies and interactions possible, so assuming that strategies effective
in one setting would successfully generalize to the other is unwise.
As an instructional designer, I found this article interesting because it highlights
a shortcoming in my own field. Instructional design models have been employed
for over half a century in order to reliably create effective instructional
materials. These models provide a combination of procedures and heuristics which,
if used properly, result in instruction that helps learners reach established
learning goals. For most of the models, however, the choice of delivery medium
is made late in the design process or given little attention. For example, the
most well-known instructional design model, the Dick and Carey model (Dick,
Carey, & Carey, 2001), leaves the selection of delivery medium until the
stage in which the instructional strategy is designed, after objectives have
been established and evaluation instruments developed. Morrison, Ross, and Kemp
(2004) posited in their model that instructional design proceeds in a flexible,
nonlinear manner, with decisions about any of the given elements (e.g.,
learner analysis, task analysis, objectives, sequencing) affecting decisions
about the others in a circular, iterative manner. Even in this model, however,
where delivery medium may be considered early in the design plan, the authors
give it only a superficial treatment as part of an analysis of the instructional
context. Even rapid prototyping (Nixon & Lee, 2001; Tripp & Bichelmeyer,
1990), with its emphasis on development from the early stages of a project,
gives little consideration to the relative merits or impact of different delivery
media on design decisions.
In real world design, the delivery medium is often stipulated at the very beginning
of the project, perhaps as early as the topic itself. For example, a company
that decides it needs to offer training on new procedures may specify that it
be delivered by an onsite instructor at their training center. Or, as is happening
at universities across the United States, a decision is made to offer a course
online without any consideration of how this will impact course objectives or
content. Yet, as was illustrated in Veal et al.’s article by teachers’
complaint that a course in geology should include hands-on activities, the delivery
medium can affect what objectives are set for the course, what instructional
strategies are used, and how assessment is conducted. As a result of the lack
of attention to the impact of the delivery medium on the choices an instructor
or an instructional designer must make, we are ill equipped to make good use
of what we already know about best practices in the design of online courses.
Finally, as a researcher of instructional innovations, I believe that Veal
et al.’s choice of a design-based research methodology bears consideration.
Especially because of the speed at which distance education is becoming widespread
and the lack of an existing body of adequate research on this topic (Moore,
Winograd, & Lange, 2001), a research methodology that examines innovation
as it happens is needed.
In the remainder of this commentary, I offer my own views on two topics relevant
to Veal et al.’s article. First, I draw on the concept of affordances
to consider which instructional strategies that have been shown to be effective
in face-to-face classes are likely to be effective in online courses and where
we might look for some differences. Second, I examine the research methodology
they use in more depth, commenting on what I see as its profound potential to
provide meaningful insights on how to impact learning in online courses.
Drawing on Best Practices in Traditional Classes
As with any innovation, we must ask how much of what we already know is applicable
to the new conditions it creates. For distance education, how much of what we
know about good instruction in traditional face-to-face settings is relevant
to online settings? Is “good” instruction good in any setting? Veal
et al. argued that simply “importing existing classroom-based models of
instruction to an online format is not appropriate,” yet they rightly
draw heavily on these existing models to find methods of enhancing their online
course.
To hypothesize about which practices shown to be effective in face-to-face
settings are likely to also be effective in online courses, a comparison of
the two would seem to be in order. It is necessary, however, to start with a
disclaimer. Such a comparison can seemingly reduce instruction into constituent
parts, giving the false impression that we educators can help ourselves, smorgasbord-style,
to whatever instructional moves seem most expedient. This is not the case. The
use of a variety of instructional strategies together creates a synergy, resulting
in a greater impact than can be accounted for by any one strategy used independently.
Therefore, it is necessary to use such a comparison between face-to-face and
online settings only as a starting point for investigation, submitting the hypotheses
it offers to rigorous examination and building along the way new understandings
of how a particular strategy interacts with the instructional approach as a
whole.
With that limitation in mind, let us compare face-to-face and online instruction.
Rather than viewing them only as alternate methods of conveying information,
it is necessary, as Jonassen, Campbell, and Davidson (1994) argued, to examine
each medium for the ways in which its affordances can be exploited to facilitate
learners’ construction of knowledge. Affordances are the properties of
a given object or environment that it offers to those who use it (Gibson, 1977).
For example, water affords floating to objects less dense than it is. A chair
affords sitting and reaching objects higher than one’s grasp. For the
purposes of this comparison, I examine online courses similar to the one described
by Veal et al. Such classes make use of a web site with links to a variety of
resources on other sites and some type of conferencing software (e.g., WebCT,
FirstClass, discussion boards) that allows interaction among the members of
the class and the instructor. This comparison could, of course, be extended
to classes that utilize other technologies, such as videoconferencing.
Online classes afford many of the same instructional strategies as face-to-face
classes. For example, both make use of well-structured text to present information.
Therefore, we might expect several of the enhancements that Veal et al. used,
such as advance organizers and review sections, to be effective in both settings,
which their study suggested to be the case. In contrast, face-to-face classes
afford the easy distribution and sharing of equipment and other materials needed
in hands-on activities. They also afford observation of students’ actions
by an instructor, with flexible questioning and feedback between the two that
can correct or extend students’ performance. Online courses do not readily
offer these affordances, as a result, impacting the types of hands-on activities
that can be used and perhaps whether they can be used at all. Thus, our understanding
of how to support active learning based on research conducted in face-to-face
classes may differ for online classes. Recognizing this fact can help us to
anticipate the types of decisions an instructor will make and the subsequent
complaint Veal et al. reported about a lack of hands-on activities.
So what else do these two settings have in common that would lead us to expect
the instructional strategies gleaned from research on face-to-face classes to
be effective in online classes? The similarities are actually far greater than
the differences. Both afford the use of multimedia – video, audio recordings,
and static images coordinated with narration can be used to gain attention,
activate prior knowledge, and present information effectively in both settings.
The use of multimedia in online classes requires a greater front-end investment
of time for development, but once created, it can be reused, whereas a lecture
with slides must be repeated each time a course is offered. Demonstrations are
also afforded by both, though they are likely to be live in one setting and
videotaped in the other. Instructor modeling, which is a key strategy in a cognitive
apprenticeship approach (Collins, Brown, & Newman, 1989) can easily be accomplished
through video. And a whole host of strategies that are effective in helping
learners process verbal information (whether presented orally or in text) should
work equally well in both settings. These include mnemonics, paraphrasing, outlining,
categorizing, self-questioning, and the use of diagrams.
Still, there are affordances offered by a face-to-face delivery method that
are unavailable or awkward for use in online classes. The rapid exchange of
ideas possible in a face-to-face class is only available if the online instructor
schedules “live” sessions, an option which is still awkward if only
text-based conferencing is used. Though still possible, a Socratic dialog may
suffer in the slow exchanges characteristic of asynchronous discussions. In
the example of modeling given above, it is far more difficult to support student
questioning about the modeling in online classes than in face-to-face ones (though
repetition of the modeling is much easier, as video places this under student
control). Coaching, another instructional strategy advocated in the literature
on cognitive apprenticeship, in which the instructor watches the learners’
early performances and provides feedback and suggestions, is more likely to
be used in face-to-face classes than in online ones, because face-to-face courses
readily afford observation of student performances.
It is easy to assume during this early period of distance education that face-to-face
classes offer more affordances to support instruction and learning. Yet in my
own teaching, I have found that online courses offer a number of affordances
not available in face-to-face classes, ones I would be loathe to part with.
I’ve come to view face-to-face classes as too constrained by time to permit
adequate reflection by students. Also, face-to-face classes are, in my opinion,
marred by power structures in which some students dominate discussion while
others remain silent. When the instructor requires participation in an online
class, all students are afforded “air time,” and as students come
to realize which of their peers post the most interesting messages, the “voices”
that are heard best are the ones who have earned the greater share of attention
through their thoughtfulness rather than their tenacity. Among the other affordances
offered by an online format that I have come to find indispensable are as follows:
- Peer feedback. In face-to-face classes, students may receive limited peer
feedback during class, but this is far more manageable in online courses.
Because students can view each other’s work for as long as they please
and because the feedback they provide is written, students benefit both from
the reflection necessary to give feedback and the new insights they gain from
the feedback they receive. Also, as with discussions, all students are involved
in peer feedback in online classes, not just those who are most likely to
speak up in class.
- An archive of participation. Because students’ contributions to discussion
in an online class are written, there is an archive of their work. I have
found this useful for assessing the thinking and contributions of individual
students, as well as for identifying emerging understandings and misconceptions
in the class as a whole.
- Interactivity. Multimedia is most effective when it offers individual learners
control over its pace, sequence, and content displayed. In a face-to-face
class, the instructor controls these elements, meaning that learners are passive
recipients of this information rather than active decision makers about what
they will view, when, and for how long.
- Repeated viewings of demonstrations. Live demonstrations have the advantage
that the learners can ask questions and the instructor can adjust the demonstration
to manage difficulties. Videotaped demonstrations have the advantage of allowing
students to view the demonstrations as many times as they need to in order
to learn the skill. I’ve found the latter particularly useful in that
most student questions are resolved simply by seeing the demonstration multiple
times and referring back to it as they attempt to apply a skill themselves.
Evidence of the value of these affordances and their effect on learning have
yet to be examined sufficiently, so it would be premature to offer prescriptions
for the design of online courses based on them. Yet, the similarities between
face-to-face and online classes suggest that many of the instructional strategies
effective in one setting are likely to be effective in the other, while the
differences between them suggest that online courses may afford new strategies
that can benefit learning. It is still necessary, as Veal et al. pointed out,
to conduct research to test the benefits of existing strategies, as well as
investigate new ones. Simply relying on research conducted in one setting to
inform the other ignores the holistic nature of teaching and learning and the
impact changing any aspect of instruction has on its quality as a whole. Also,
such a research agenda can be used not only to inform the design of online courses
but also better define the conditions under which a given instructional strategy
is effective.
Investigating Innovations: Design-Based Research
Veal et al. used a “design study approach,” to investigate their
course enhancements across two phases of their study, with the results of Phase
1 informing the design of Phase 2. This approach, also called “design-based
research” (The Design-Based Research Collective, 2003) and “design
experiments” (Brown, 1992), is an emerging methodology for the examination
of interventions in which development and research take place within several
cycles of design, use, analysis, and redesign. The purpose of this iterative
process is not only to enhance the particular intervention being investigated
but to also develop theories to account for the impact of the intervention and
models to inform the design of other innovations. This approach has garnered
great interest recently, with a theme issue of Educational Researcher
being devoted to it (Kelly, 2003).
This approach holds a number of potential advantages for the investigation
of online classes. First, because design-based research investigates innovations
as they evolve within real-world settings, it reflects the way in which online
courses evolve as instructors design, analyze, and redesign their courses. This
process of evolution in online courses will be especially strong in the foreseeable
future, both as new research impacts practice, and, more dramatically, as new
technologies make new practices possible. This necessary evolution in course
design can best be examined through a methodology aimed at deriving insights
across multiple iterations of an innovation.
Second, a major thrust of research-based design is the development of theories
for how learning occurs in specific situations (Cobb, Confrey, diSessa, Lehrer,
& Schauble, 2003). As researchers collect data about conditions created
by an innovation and the impact of that innovation on learning, motivation,
or other constructs, patterns emerge that suggest how the innovation functions
within the environment and why this occurs. These patterns can lead to theories
about how learning occurs in online settings capable of informing designers
of these classes about specific conditions conducive to learning or specific
supports instructors can use to advance student thinking in online settings.
These theories, as Cobb et al. (2003) pointed out, are likely to be quite humble,
targeting only limited settings, but this is exactly the type of understanding
that can help us to recognize how online settings differ from face-to-face ones
and the impact of this on decisions about instructional strategies.
To illustrate how design-based research might work in online classes, I offer
an anecdote from my own experiences teaching online that could best be investigated
using this methodology. Online discussion is a key instructional strategy in
one of my classes, and in order to get students to look at this approach from
multiple perspectives, each student serves as a facilitator for one of the units
of the course. As part of that role, students evaluate their peers’ contributions
to the discussion. The goal of facilitation is for students to reflect meaningfully
on what constitutes high quality participation, both so they can become better
participants and so they can support quality interaction in future settings
where they collaborate online.
For a variety of reasons, the quality of discussions in my class varied widely
by group. To address that, I worked with facilitators to develop the rubric
shown in Table 1 to assess student participation. This
rubric included five categories for evaluation, with four possible levels of
performance described within each category. One of these levels was “Exceeds
Expectations.” Students did not receive extra credit for exceeding expectations,
but this level was included in the rubric so that facilitators could acknowledge
excellence. The rubric was revised with successive groups of facilitators. The
interesting result was that the quality of the online discussions rose dramatically,
with most students rightfully being evaluated as exceeding expectations in most
categories. Why?
My informal theory is that the rubric (a) helped clarify expectations and define
excellence in online discussion and (b) caused the facilitators to reflect on
the nature of effective interactions, which made them better participants in
subsequent units. This is indeed a modest theory, but if supported, it could
in turn support theories about the role reflection and peer evaluation plays
in enhancing performance or becoming a member of a community of practice. A
study employing a design-based research approach could examine the impact of
this rubric as it evolved across the semester, collecting data on changes in
the content of students’ postings and their conceptions of what constitutes
quality discussions. The rich data would provide a much better basis for a theory
as to the impact of the rubric and perhaps as to ways to best encourage substantive
participation in online discussion.
My anecdote also illustrates a potential problem with design-based research:
It is easy to slip into anecdotal evidence and make causal claims precipitously.
Shavelson, Phillips, Towne, and Feuer (2003) emphasized the paramount importance
of ruling out competing hypotheses before making knowledge claims and argued
that design-based research is particularly vulnerable to problems in this area,
because it is used to investigate innovations in complex environments. In real
world educational environments, literally dozens of variables are in play in
any given situation. This is certainly the case for online courses, where the
demands of the content are further burdened by issues related to distance technologies
and students’ lack of experience with the format.
For example, in my anecdote, could experience with the online format and peer
modeling of quality contributions to online discussion account for improvements
in the discussions across the semester? Did students simply find more to say
about readings in later units than in earlier ones? A rigorous investigation
of the impact of the rubric on participation would need to examine these competing
hypotheses. For this reason, design-based research is best conducted across
several studies, with different studies approaching the issue in different ways
and with the results of each study informing the next. For example, after the
rubric is refined in early studies, setting up an experiment in which a group
using the rubric is compared to a control group not using it could establish
a basis for claims of causality. Examining its impact in other classes that
employ extensive online discussions would support claims of generalizability.
Such a line of research could contribute to an understanding of best practices
in online classes and theories of how online learning is best supported.
Veal et al. collected data suggesting that teachers found their enhancements
to an online course to be effective and useful to their own teaching and which
offered some insights into which enhancements were most effective. Additional
data from interviews and observations over the course of the class might have
yielded a more robust understanding of how these enhancements impacted the ways
in which teachers worked in the course and made it possible to begin to develop
hypotheses about ways in which teachers develop content knowledge on geology
in online classes and how course design can best support it. Developing such
hypotheses is an important goal in design-based research and could guide future
investigations that could lead to strong knowledge claims.
In conclusion, the rapid growth of online education has created a gap between
research and practice, with our need for understanding of effective practices
in online settings outstripping our knowledge. As Veal et al. pointed out, existing
knowledge based on research conducted in traditional settings is a good starting
point for finding ways to enhance online learning, but it is not sufficient.
Likewise, a comparison of the different affordances offered by different settings
can help us identify instructional strategies that are likely to be as successful
in one setting as another. It remains necessary to examine those strategies
in the new setting in order to develop understandings about how they impact
learning and how to implement them effectively. Design-based research is emerging
as an effective methodology for studying these types of innovations in action,
but for this methodology to yield credible knowledge claims and theories, a
rigorous line of research, with each study laying the groundwork for the next,
is necessary.
References
Brown, A. L. (1992). Design experiments: Theoretical and methodological challenges
in creating complex interventions in classroom settings. The Journal of
the Learning Sciences, 2(2), 141-178.
Cobb, P., Confrey, J., diSessa, A., Lehrer, R., & Schauble, L. (2003).
Design experiments in educational research. Educational Researcher, 32(1),
9-13.
Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship:
Teaching the crafts of reading, writing, and mathematics. In L. B. Resnick (Ed.),
Knowing, learning and instruction: Essays in honor of Robert Glaser.
Hillsdale, NJ: Lawrence Erlbaum Associates.
The Design-Based Research Collective. (2003). Design-based research: An emerging
paradigm for educational inquiry. Educational Researcher, 32(1), 5-8.
Dick, W., Carey, D. M., & Carey, J. O. (2001). The systematic design
of instruction (5th ed.). New York: Longman.
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(Eds.), Perceiving, acting, and knowing (pp. 67-82). Hillsdale, New
Jersey: Lawrence Erlbaum Associates.
Jonassen, D. H., Campbell, J. P., & Davidson, M. E. (1994). Learning with
media: Restructuring the debate. Educational Technology Research and Development,
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New York: McGraw Hill.
Morrison, G. R., Ross, S. M., & Kemp, J. E. (2004). Designing effective
instruction. Hoboken, NJ: John Wiley & Sons.
Nixon, E. K., & Lee, D. (2001). Rapid prototyping in the instructional
design process. Performance Improvement Quarterly, 14(3), 95-116.
Shavelson, R. J., Phillips, D. C., Towne, L., & Feuer, M. J. (2003). On
the science of education design studies. Educational Researcher, 32(1),
25-28.
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instructional design strategy. Educational Technology Research and Development,
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Veal, W., Brantley, J, & Zulli, R. (2004). Developing an online geology
course for preservice and inservice teachers: Enhancements for online learning.
Contemporary Issues in Technology and Teacher Education [Online serial], 3(4).
Retrieved July 23, 2004, from http://www.citejournal.org/vol3/iss4/science/article1.cfm
Susan Pederson
Texas A&M University
email: spedersen@coe.tamu.edu
Table 1
Rubric Used to Assess Student Participation in an Online Discussion
| |
Exceeds Expectations |
Meets Expectations |
Falls Short of Expectations |
Does Not Meet Expectations |
| Quality of initial postings |
student's initial responses to two stimulus questions were
original and insightful and provided rich material for group discussion |
student provided original and thoughtful responses to two
stimulus questions |
student provided a response to two stimulus questions, but
the responses did not show depth of understanding of the readings or they
merely echoed ideas already expressed by other group members; or student
provided an initial response to only one of the stimulus questions |
student did not post initial responses to the stimulus questions
or posted brief, superficial responses |
| Rate of participation |
student participated five or more days, making substantive contributions
on most of those days |
student participated on at least three different days spread throughout
the discussion |
student participated in discussion, but postings are either not on three
different days or are bunched at the beginning or end of the unit |
student participated on only one day or not at all |
| Integration of the readings |
student demonstrated a profound understanding of the readings by integrating
numerous concepts from them across most of the messages he or she posted |
student integrated concepts from the readings into the discussion in a
meaningful way in at least 4 different messages |
student made fewer than 4 meaningful references to the readings; references
to the readings were superficial |
student refered to readings less than two times and only in a superficial
manner |
| Interaction with groupmates |
after the initial postings, student posted 4 or more substantive messages
that elaborated on or provided a contrasting view with ideas contributed
by group mates |
student responded to others' contributions in at least 2 substantive messages
and 2 shorter messages |
student responded to others' contributions by asking questions or agreeing
with points made, but fewer than two of these responses were substantive |
student did not respond to others' contributions |
|