Content uploaded by Minjuan Wang
Author content
All content in this area was uploaded by Minjuan Wang on Aug 21, 2014
Content may be subject to copyright.
Chapter 11
CYBERGOGY FOR ENGAGED LEARNING:
A FRAMEWORK FOR CREATING LEARNER
ENGAGEMENT THROUGH INFORMATION
AND COMMUNICATION TECHNOLOGY
Minjuan Wang1 and Myunghee Kang2
1San Diego State University, USA; 2Ewha Womans University, Korea
Abstract: The continued and growing need for new learning opportunities,
linked with newer information systems and communication technologies, has
pushed online learning into the center of the discussion of educational
practice. There is a need to establish a framework for generating meaningful
and engaging learning experiences for distance students with diverse cultural
and linguistic backgrounds. We coin the term “Cybergogy” as a descriptive
label for the strategies for creating engaged learning online. Our model of
Cybergogy for Engaged Learning (see Figure 1) has three
overlapping/intersecting domains: cognitive, emotive, and social. This model
is a synthesis of current thinking, concepts, and theoretical frameworks on the
extent and nature of the three domains in learner engagement online. We
argue that engaged learning will occur when the critical factors in each
domain are well attended, so as to encourage learners’ cognitive, emotive,
and social presence. We created this model particularly for online settings
that involve more generative and constructive learning activities. Thus,
instructors can use this model to profile each learner and then design tactics to
engage individuals accordingly, a process we call “customized engagement.”
As a consequence, learners will not only have the opportunity to accomplish
their learning goals, but also will be actively involved in the learning process.
Key words: cybergogy, engaged learning, online presence, instructional design, online
facilitation
1. CYBERGOGY MODEL AND INDICATORS OF
ENGAGEMENT IN ONLINE LEARNING
1
On line Le arnin g En vir onm en t
Enga ged
Lear n in g
Cogn itiv e
fa ctor s
Em ot iv e
fa ctors
Social
fa ctors
•Prior knowledge/Experience
•Achievement goals
•Learning activity
•Cognitive/learning style
•Feeling of self
•Feeling of community
•Feeling of learning
atmosphere
•Feeling of learning
process
•Personal attributes
•Context
•Community
•Communication
On line Le arnin g En vir onm en t
Enga ged
Lear n in g
Cogn itiv e
fa ctor s
Em ot iv e
fa ctors
Social
fa ctors
•Prior knowledge/Experience
•Achievement goals
•Learning activity
•Cognitive/learning style
•Feeling of self
•Feeling of community
•Feeling of learning
atmosphere
•Feeling of learning
process
•Personal attributes
•Context
•Community
•Communication
Figure 1. The “MM” Model: Cybergogy for Engaged Learning
In any learning environment, truly engaged learners are behaviorally,
intellectually, and emotionally involved in their learning tasks (Bangert-
Drowns & Pyke, 2001). Engagement is a multidimensional phenomenon that
varies from setting to setting: time-on-task, self-regulated learning,
intrinsically motivated involvement of integrated cognitive process, learning
environment (quality of the dialogue), and production of tangible results
(Bangert-Drowns & Pyke, 2002). For K-12 schools that use computer
technologies in teaching, Jones and his/her colleagues (1995) identify vision,
tasks, assessment, instructional model, learning context, grouping, teacher
roles, and student roles as the indicators of engaged learning.
Here we regroup indicators discussed in the literature to derive the
taxonomy of engagement and assessment strategies in online learning. Table
1 (see appendix A-Taxonomy of Forms of Engagement and Assessment
Strategies) displays several forms of engaged learning online, their
indicators, and ways to assess each form of engaged learning. The taxonomy
qualifies forms of engagement and assessment strategies.
Below we examine each of the three domains and suggest a cybergogy
for engaging learners through activating cognitive, emotive, and social
factors. For instance, we explore ways that instructors can use to detect
learners’ emotional cues and cultivate their positive feelings; to increase
learners’ self-confidence and arouse their curiosity through course design
2
and e-facilitation; to conduct online communication and build a supportive
learning environment.
2. COGNITIVE FACTORS
Cognitive domain points to the factors that initiate an individual’s
construction of knowledge. It investigates the way an individual optimizes
personal relevance and meaning through the knowledge construction
process. Knowledge construction has been researched in cognitive sectors as
well as constructivist sectors. Information processing theory, as a part of
cognitive psychology, envisions the human mind as being similar to a
computer processor and explains psychological events in terms of the input,
process, storage, and output of information. Self-regulated learning theory
explains learning as a form of cognitive engagement, such as a learner’s
intellectual involvement in planning and monitoring, when performing tasks
in classroom.
According to this theory of cognitive engagement, knowledge
construction has three major stages: information acquisition, information
transformation, and knowledge construction. In the information acquisition
stage, learners review their own knowledge structure, which in turn
stimulates their interest in finding useful information and in exploring and
transforming external stimuli. In the information transformation stage,
learners select appropriate information, organize and integrate it with
existing knowledge, and plan for specific activities. The final destination is
the knowledge construction stage, where the products of knowledge
construction are realized. The knowledge that is constructed is not the type
that is the result of rote memorization, but a kind that could be applied in
new circumstances, used to solve problems, and used in relationship with
other elements in the context. The following factors are thought to affect an
individual’s knowledge construction during the process: prior
knowledge/experience, learning goals, learning activities, locus of control,
and assessment style (Hannafin et. al., 2003).
However, constructivists have defined knowledge construction as the
extent to which learners are able to construct and confirm meaning through
sustained discourse in a critical community of inquiry (Garrison et al., 2003).
In their view, knowledge construction is a circular process of conception,
experience, perception, and judgment, in which major roles are played by
practical inquiry of the stages of resolution, triggering event, exploration,
and integration. From this perspective, it is assumed that knowledge
construction could be greatly assisted by a tool to assess critical discourse
and reflection for the purpose of acquiring intended and worthwhile learning
outcomes.
3
For both approaches, interrelated factors relating to cognitive processes
and outcomes are considered to be important in cognitive domain. Learners’
prior knowledge, their goals and learning tasks, and their cognitive styles are
important factors. Therefore, learning designers should enhance their
abilities to consider these factors as a means of making the learning most
relevant to students. In addition, instructors could also use this knowledge to
set course goals, design activities, select the methods of delivery, and
generate appropriate assessment.
3. PRIOR KNOWLEDGE/EXPERIENCE
Included in the model’s cognitive domain, prior knowledge is important
when enhancing the learning experience. A large body of findings shows
that learning proceeds primarily from prior knowledge, and only secondarily
from the presented materials. Moreover, when a new curriculum is related
to existing knowledge and skills, learners are usually more interested.
Learning is promoted when existing knowledge is activated as a foundation
for new knowledge (Merrill, 2002). Learning takes place when students
process new information. Several factors, such as students’ prior knowledge,
values, expectations, and the learning environment, heavily influence their
learning process (Newmann et al. in Brown, 1997).
Ironically, to effectively integrate prior knowledge into a teaching plan,
an instructor must address defects in existing knowledge that may interfere
with learning new concepts. Research has shown that a learner's prior
knowledge often confounds an educator's best efforts to deliver ideas
accurately. Learners will distort presented material if it is at odds with their
prior knowledge. Neglect of prior knowledge can result in the audience
learning things opposed to the educator's intentions, no matter how well
those intentions are executed in an exhibit, book, or lecture.
4. ACHIEVEMENT GOALS
Allowing students to set their learning goals could boost motivation and
thus encourage their immersion in the learning process. Once expectations
and goals are clearly set, the instructor can then select the best methods of
delivery and the type of assessment to evaluate performance. Any type of
course assessment can be used as long as they align with and are consistent
with both the instructional methods used and the student learning objectives
(SLOs) for the course.
Dweck and Leggett (1988) identify two types of achievement goals-
performance and learning - that affect students' academic performance.
Performance goals are associated with the desire to achieve favorable grades
4
and social approval. Performance-oriented students are typically concerned
with the outcome rather than with the actual process of learning and are
more likely to subscribe to an entity theory of intelligence, believing that
intelligence is a fixed attribute. Students with performance goals tend to
perform well on easier tasks for which a positive evaluation can be achieved,
but they often become discouraged and give up easily when faced with a
difficult task, attributing their failure to a lack of ability. In contrast,
learning-oriented students are interested in new material and they tend to
subscribe to the incremental theory that intelligence is malleable. These
students display "mastery-oriented" behavior, showing more persistence on
difficult tasks, using alternative strategies, and attributing failure to a need to
work harder rather than to a lack of ability (Heyman & Dweck, 1992).
Dweck introduces the idea of learning and performance goals as a
unidimensional variable (Dweck & Leggett, 1998). Roedel and his
colleagues, (1994), however, suggest that learning and performance goals
seem to be independent of one another. Thus, a person may be high in both
learning and performance goals, low in both of the goals, or high in one and
low in the other. Eppler and Harju (1997), using Roedel's scale, divide
college students into four categories of goal patterns: low on both learning
and performance goals; high on both learning and performance goals; high
on performance goals while low on learning; and high on learning goals
while low on performance. In their study, students who endorsed learning
goals only or who endorsed both learning and performance goals had
significantly higher GPAs than the group with low levels of goal orientation.
This study therefore supports Dweck's hypothesis about goal orientation
being predictive of academic success.
Goal orientation does not seem to influence student performance in low-
stress conditions. However, when faced with stress, such as failing to pass an
exam, learning-goal dominant students can persevere and adopt more
successful learning strategies. By contrast, performance-goal dominant
students can perform more poorly or engage in irrational behavior, such as
giving up but not dropping the class. Hoyert and O'Dell report that these
results often occur when students perceive learning and performance goals
as competitive factors, rather than as continuous or independent factors.
5. LEARNING ACTIVITY (TASK AND ASSESSMENT)
To stimulate engaged learning, tasks need to be challenging, authentic,
and multidisciplinary. Such tasks are typically complex and involve
sustained amounts of time. They are authentic in that they correspond to the
tasks in the home and workplaces of today and tomorrow. Collaboration
around authentic tasks often takes place with peers and mentors within
5
school as well as with family members and others in the real world outside
of school. These tasks often require integrated instruction that incorporates
problem-based learning and curriculum by project.
Assessment of engaged learning involves presenting students with an
authentic task, project, or investigation, and then observing, interviewing,
and examining their presentations and artifacts to assess what they actually
know and can do. This assessment, often called performance-based
assessment, is generative in that it involves students in generating their own
performance criteria and playing a key role in the overall design, evaluation,
and reporting of their assessment. The best performance-based assessment
has a seamless connection to curriculum and instruction so that it is ongoing.
Assessment should represent all meaningful aspects of performance and
should have equitable standards that apply to all students.
6. COGNITIVE AND LEARNING STYLE
In an extensive overview of the work on learning and cognitive styles
over the past 30 years, Riding and Rayner (1998) attempt to classify and
integrate much of the earlier work. They argue that many of the different
labels used to categorize cognitive styles and learning styles were “different
conceptions of the same dimension”. After comparing and contrasting a
range of classifications, they identify two major cognitive style dimensions:
Verbal-Imagery - an individual’s position on this dimension
determines whether that person tends to use images or verbal
representation to represent information when thinking.
Wholist-Analytic - an individual’s position on this dimension
determines whether that person processes information in parts or
as a whole (Riding & Rayner, 1998).
Kolb (1984) proposes a theory of experiential learning that involves four
principal stages: concrete experiences (CE), reflective observation (RO),
abstract conceptualization (AC), and active experimentation (AE). The
CE/AC and AE/RO dimensions are polar opposites as far as learning styles
are concerned, and Kolb postulates four types of learners, depending upon
their position on these two dimensions: According to Kolb (1984), the four
basic learning modes, correspond to four basic learning styles: pragmatist,
reflector, theorist, and activist. These learning styles display the following
characteristics: (1) Pragmatist. The pragmatist learning style depends mainly
on the dominant learning capacities of active experimentation and abstract
conceptualization. (2) Reflector. This style depends mainly on concrete
experience and reflective observation; it has great advantages in imaginative
6
abilities and awareness of meaning and values. (3) Theorist. The theorist
learning style depends mainly on abstract conceptualization and reflective
observation. This style has great advantages in inductive reasoning, creating
theoretical models, and assimilating different observations into an integrative
entity. (4) Activist. This style depends mainly on active experimentation and
concrete experience; it has great advantages in doing things, implementing
plans, and engaging in new tasks (Thorne, 2003).
7. EMOTIVE FACTORS
It is commonly known that teaching and learning work best in a
classroom atmosphere of mutual affection and respect, rather than in one of
fear and intimidation. However, the western scientific community tends to
dichotomize cognition and emotion (McLeod, 1991). In adult education, for
instance, theory and practice often marginalize emotions and elevate
rationality; the ability to reason has always superseded emotions (Dirkx,
2001). Teaching and learning are often framed as largely rational and
cognitive; emotions are perceived as either impediments to learning or only
motivators of it (Dirkx).
Recently, a growing body of literature (e.g., Currin, 2003; Dirkx; Hara &
Kling, 2000; O’Regan; Kort, Reilly & Picard, 2003; Weiss, 2000) has begun
to espouse the central role of emotion to any learning endeavor and
outcomes, especially in e- or online learning. Dirkx argues for the power of
feelings (emotion and imagination) in adults’ meaning-construction. Once
considered “baggage” or “barriers” to learning, emotions and imagination
are now perceived as integral to the process of adult learning (Dirkx, p. 67).
Continuous and increasing exploration of the complex set of parameters
surrounding online learning reveals the importance of the emotional states of
learners and especially the relationship between emotions and effective
learning (e.g., Kort, Reilly & Picard; O’Regan). Kort and his colleagues
(2001) find that in a technology-based environment, learners commonly
experience emotional changes during their learning journey. From frustration
to excitement, from boredom to fascination; the emotive dimensions of
learning could contribute to a positive educational experience or attribute to
a negative one. The efficiency and effectiveness of learners’ information
processing can be affected by the range of emotions emerging from the
learning process.
A few have also attempted to create models connecting emotions with
either social factors or cognitive process. For instance, Martinez devises a
model of online learning orientations, which recognizes a dominant
influence of emotions, intentions and social factors on how individuals learn
differently” (in O’Regan, p. 3). Kort and his colleagues propose a model
7
relating the cognitive dynamics of the learning process to the range of
various emotional states (see Figure 2).
Figure 2. Proposed model relating phases of learning to
emotions (reprinted with the authors’ permission)
Our Cybergogy for Engaged learning is unique in its synthesis of
constructs from the existing model and in its interweaving the factors in the
affective domain (primarily emotions and feelings) with both cognitive and
social dynamics of the learning process. Thus, this model provides a more
systematic and holistic view of factors that cultivate engaged learning.
The understanding of emotions is diverse and multifaceted, from Darwin
to behaviorist representation, from physiological to psychological terms.
Here emotions are defined from the social-cultural perspectives as “social
acts involving interactions with self and interactions with others” (Denzin in
O’Regan, p. 7). In essence, emotion is “a transitory social role” that exists in
both an interpersonal and a socio-cultural context (Averill, p. 7). To address
emotions more clearly and expansively, we identify four kinds of feelings
that might affect learner engagement: a) feelings of self, b) feeling of
interpersonal connection/community, c) feelings of learning atmosphere, and
d) feelings emerging from the learning process.
8. FEELINGS OF SELF (CONFIDENCE, COMPETENCE,
EFFICACY (with online communication and technological tools)
8
Dirkx (2001) concludes from empirical data that “emotions and feelings
play a critical role in our sense of self and in processes of adult learning. . . .
Emotions always refer to the self, providing us with a means for developing
self-knowledge” (p. 64-65).
Feelings of self affect learner engagement through motivation. Ample
research (Bandura & Cervone, 1986; Locke, Frederick, Lee, & Bobko, 1984;
Schunk, 1990) has revealed that learners’ perceived self-efficacy, self-
confidence, and competence with the learning tasks directly affect their goal-
setting and thus their motivation to engage in the learning process. Some
(e.g., Lumpe & Chambers, 2001) find that learners’ self-efficacy beliefs can
be significant predictors of their performance of a task; they argue that a
learner can actively engage in the learning process, only if the learner feels
that a task is achievable and manageable.
Feelings of self-confidence and efficacy can help students adapt to online
learning, which provides them with more opportunities to be engaged in self-
paced learning (Katz, 2002). As a result, they might be able to overcome the
desire for face-to-face interaction, a habit of learning that is carried over
from the traditional classroom learning.
The effect of self-confidence on learner engagement is supported by
Keller’s ARCS model with which he identifies four key learning motivation:
attention, relevance, confidence, and satisfaction. Among them, confidence
is essential because “people have a desire to feel competent and in control of
key aspects of their lives” (Keller, n.d., p. 381). A perception of control
decreases stress and leads to healthier, happier behavior.
9. FEELINGS OF INTERPERSONAL CONNECTIONS AND
COMMUNITY
Besides feeling good about themselves, learners also need to feel
positively about the broader social world. Engagement requires a sense of
“fitting-in” the larger learning environment. The feeling of belonging to a
community contributes to students’ motivation, involvement, and
satisfaction with the learning process (Chan & Rapman, 1999; Wegerif,
1998 in Oren, Mioduser, and Nachmias, 2003).
Socialization, the establishment of a social network and the building of
learning communities, has been considered essential for a fun and successful
learning experience in technology-mediated learning situations (Rovai,
2001; Preece, 2000). Online communities are social aggregations that
emerge from the web when enough people carry on public, lengthy
discussions, with sufficient human feeling, to form webs of personal
relationships (Rheingold, 2000). The burgeoning literature on online
learning communities has generated conclusive findings about the
9
importance and impact of communities on students’ engagement,
satisfaction, and learning outcomes. In a study of social dimensions of
asynchronous learning networks, Wegerif (2003) concludes that “individual
success or failure on the course depended upon the extent to which students
were able to cross a threshold from feeling like outsiders to feeling like
insiders” (p. 34). Although a few studies (e.g., Beaudoin, 2002; Fritsch,
1997) have found that witness learners or “lurkers” who refrain from visible
interactivity still meet learning objectives, nearly all of the literature
indicates that socializing is essential for a fun and successful learning
experience in technology-mediated learning situations.
Our Engaged Learning Model predicts that feelings of community or
isolation can be the consequence of activities or lack of activities in the
social domain. Strategies to help students enter the learning community and
to sustain learning communities are further discussed in the social dimension
section.
10. FEELING OF LEARNING ATMOSPHERE (safe and positive
versus fearful; open negotiation versus domination)
Engagement in classroom settings is closely tied to the larger learning
environment, such as the quality of interaction and the culture of the college
campus (Bangert-Drowns & Pyke). This aspect of engagement, we believe,
can be more important in online settings. "People who feel unsafe,
unconnected, and disrespected are unlikely to be motivated to learn"
(Wlodkowski & Ginsberg, 1995, p. 2). Building a supportive learning
environment, increasing students' awareness of diversity, and facilitating
student-student communication are strategies conducive to success
(Wlodkowski & Ginsberg).
Quality interaction among students and instructor are conducive to a
positive learning atmosphere, one that is marked by socializing, rapport,
connections, debates, and open negotiation. This emphasis for interaction is
rooted in social constructivism (Vygotsky, 1986), which holds that shared
knowledge develops through joint communication and activity.
Communication among online participants facilitates building a community
of learners that shares understanding and adopts a common knowledge base
(Wang, 2001).
Besides, an instructor must attend to many cognitive factors to develop a
positive and supportive learning atmosphere. For instance, the instructor
must treat students as individuals by modeling respect for individual
differences and by taking into account the expectations and experience of
students with different needs (Wlodkowski & Ginsberg, 1995). Learning
opportunities need to be created to suit students’ different learning styles;
presentation styles and assignment requirements must be varied to
10
accommodate students’ different talents and learning styles (Hutchines,
2003).
11. FEELINGS EMERGING FROM THE LEARNING
PROCESS
Students often experience a range of emotions while learning online such
as interest/curiosity, confusion/anxiety/frustration, fascination or boredom,
pride, and satisfaction or dissatisfaction. The most common feelings --
frustration, isolation, anxiety, and confusion -- are often caused by the online
environment itself, including communication breakdowns and technical
difficulties (Hara & Kling, 2000). Other factors in the cognitive and social
domain, such as technological and pedagogical problems, information
overload, and social isolation, can also contribute to this frustration.
Therefore, effective facilitation in the cognitive and social domains can help
reduce negative emotions and cultivate positive ones. In particular, a feeling
of satisfaction is essential to the student learning process. In their meta-
analysis of studies about student satisfaction in on-line courses, Hill and
his/her colleagues (1996) find that students who felt most satisfied (or had
the highest level of “perceived learning”) interacted with online classmates
at a deeper level and participated more actively in their online sessions.
Kort and his colleagues describe learners’ emotional changes during the
learning journey as taking place in several zones: the zone of curiosity, the
zone of anxiety, the zone of flow, and finally the zone to a productive path.
Based on their model of emotion-learning (see Figure 2), they hope to devise
a computer-based system that has the artificial intelligence of expert teachers
who “are adept at recognizing the emotional state of learners and take
appropriate action that positively influences learning” (Kort et. al. 200l, p.
1). Before this system becomes a reality, however, the human teacher will
need to take actions to keep students engaged. Following we address
strategies that instructors can use to emotionally engage students in learning.
12. SOCIAL FACTORS
Social dimensions are the social acts involving interactions with self and
others. Because social domain is so broad and affects learners so profoundly,
it holds an important position in our Engagement model. The social factors
in our Engagement Model fall into the following categories:
a. Personal attributes: age and gender, language, culture, and media
literacy abilities
11
b. Learner’s social-cultural context: goals, motives, expectations,
and value (overlapping cognitive)
c. Community-building: establishing group identity, trust,
interaction, and construction of shared knowledge
d. Communication: group size, discussion content, requisite
software, and group moderation (team building, team
maintenance, performing a team)
13. PERSONAL ATTRIBUTES
Personal traits and learner expectations must be accounted for. Four sets
of opposing values help explain differences in social expectations:
individualism versus collectivism, achievement versus relationship
orientation, loose versus tight structure, egalitarian structure versus hierarchy
(Weech, 20001). Instructors need to recognize expectation differences and
take actions to align them with learning materials and activities.
14. SOCIAL CONTEXT
In the social domain, the most critical factor contributing to learning and
outcomes is the social context. The learner’s social context affects his
personal attributes, access to group discussions, and the community within
which he is engaged. Every learner possesses a background and distinct
culture that the learner will unavoidably bring to every learning endeavor.
For this reason, consideration of the social-cultural context is of supreme
importance. Often times, the method of online course delivery needs to be
shifted to better fit the socio-cultural contexts of the learner involved.
15. COMMUNITY BUILDING
Although the term “online community” is subject to a variety of
definitions, all seem to agree that a social connection is critical to online
learning. Ample studies have reiterated that individuals are embedded in
their societies and that social and cognitive skills can be enhanced by
enhancing social presence. Therefore, the sense of community is essential in
online learning for two reasons: a) working together can help students clarify
similar confusions; and b) social group can also help maintain student
interest and keep them attending to the course (Currin, 2003).
Research on learning processes in face-to-face groups indicates that
development of social climate is important to make students feel like insiders
in the learning environment, thus contributing to students’ motivation,
involvement, and contentment (Chan & Rapman, 1999; Wegerif, 1998).
12
Although early studies dealing with computer mediated relationships led to
the conclusion that the network does not contribute to the creation of a social
climate (Oren et al., 2002), more recent studies show that effectively
designed and monitored online environments can create non-alienating
social environments.
The Internet clearly transcends time and space and supports the evolution
of a dense and multifaceted social life online (Oren et al.). Social
interactions in virtual learning groups can be strongly intertwined with
learning interactions, and can evolve to respond to functional needs as the
groups’ work proceeds (Oren et al., Discussion, ¶ 5). Several contextual
factors, such as course design, characteristics of the technological media
used, and the use of moderators, could help learners enter a learning
community (Wegerif, 1998).
16. COMMUNICATION
Some other contextual factors include communication tools and group
moderation. The use of email, online conferencing, web databases,
groupware, and audio/videoconferencing significantly increases the extent
and ease of interaction among all course participants, as well as access to
information (Kearsley & Shneiderman, 1999).
17. CYBERGOGY FOR CUSTOMIZED LEARNER
ENGAGEMENT
Below we suggest tactics for creating these “customized engagements”,
mainly through increasing learners’ cognitive, emotive, and social presence
during the learning process (see Figure 3). Sample strategies discussed
include: detecting learners’ cognitive-emotive states online, recognizing and
detecting their emotional signals, selecting a course of action to respond
properly to these signals, structuring teamwork, bridging the cultural divide,
and supporting both individual and collaborative learning.
18. DESIGNING ENGAGING INSTRUCTION
Engaged learning should start from design, with instructors designing
course materials with the learners in mind, materials that are inherently
engaging. Historically, instructional designs are channeled in the direction of
leanness, clarity, and alignment of learning objectives with activities and
13
assessment. Most instructional design literature prescribes sequences that
proceed smoothly from the familiar to the strange, and do it so gradually and
Figure 3. Cybergogy for Engaged Learning: Increasing the Level of
Presence
systematically that the yet-to-be-learned is never seen as the unknown. Thus
we offer suggestions for designing more engaging activities, by using
mystery, curiosity, and appropriate activities to enhance cognitive, emotive
and social presence (see Figure 3).
19. CREATING A SENSE OF SURPRISE AND MYSTERY IN
TEACHING
The field of instructional design has failed to fully recognize the power of
mystery in the learning process. When used appropriately, mystery can
enhance learning, both cognitively and affectively. Research (Weiss, 2000)
has shown that surprise and mystery can foster emotional connections that
make a direct biochemical link with memory. Also, surprise and mystery can
help grab students’ attention, an increasing challenge for students of the 21 st
century. Known as Generation X, these students have short attention spans
(Snell, 2000) and require autonomy and flexibility of their own learning
(Brown, 1997).
To effectively engage Generation X, learning must be active and
interactive, including the use of brainstorming, concept mapping,
14
On line Learn ing Envir onm en t
Eng age d
Lea r ning
Cog n itiv e
pr e sence
Em o ti ve
pr e sence
Social
pr e sence
•Self-regulated learning
•Ownership of learning
•Generative learning
•Knowledge construction
•Feeling confident
•Feeling secure
•Feeling comfortable
•Feeling curious
•Sharing
•Cohesiveness
•Acceptance
•Collaborative
learning
On line Learn ing Envir onm en t
Eng age d
Lea r ning
Cog n itiv e
pr e sence
Em o ti ve
pr e sence
Social
pr e sence
•Self-regulated learning
•Ownership of learning
•Generative learning
•Knowledge construction
•Feeling confident
•Feeling secure
•Feeling comfortable
•Feeling curious
•Sharing
•Cohesiveness
•Acceptance
•Collaborative
learning
visualization software, and simulations that enable learners to experiment
with modeling complex ideas and concepts (Driscoll, 2002). Mystery-
embedded simulations will satisfy students’ craving for stimulation and for
immediate answers and feedback (Brown, 1997). Good teachers know this
well, and intentionally craft situations in which uncertainty is created and
resolved.
Keller’s ARCS (Attention, Relevance, Confidence, & Satisfaction) model
highlights the importance of curiosity in motivating learners (Keller &
Suzuki, 1998). The model encourages designers to increase perceptual
arousal by presenting information that is incongruous or uncertain. For
instance, to create a sense of mystery by partially revealing knowledge in a
problem-solving environment. Other tactics include encouraging learners to
generate and test hypotheses, modeling curiosity, and using giving learner
opportunities to explore their own interests (Arnone, 2003).
Incorporating hidden information into instruction and giving word-
guessing games are some other ways to increase uncertainty (Malone &
Lepper, 1987). Creating an environment conducive to inquiry further ensures
that learning will occur in the presence of mystery. Designers can integrate
creative assessment tools into instruction as well for concrete confirmation
that learning has transpired.
To summarize, we should value affective learning as highly as cognitive
learning, and see the two as interwoven. Likewise, current educational
systems must value the learner over the curriculum, and must tolerate
learning outcomes that may be less predictable but highly worthwhile.
20. MESSAGE DESIGN: AROUSING POSITIVE EMOTIONS
Instructors’ messages should build emotional connection to learning. For
example, an instructor can use messages and images that are intended to be
emotionally arousing. In particular, images can be used to represent feelings
and emotions in adult learning (Dirkx; Hillman, 1975). Dirkx proposed the
imaginal method as an alternative to “the rational and reflective process of
meaning-making” (p. 63). The essence of this method is to encourage
learners to actively engage and initiate a dialogue with their emotions
through imagination (Clark, 1997).
Using socio-culturally appropriate images could stimulate learners’
imagination and cultivate their imaginative connection with the self and the
broader social world. “Emotionally charged images, evoked through the
contexts of adult learning, provide the opportunity for a more profound
access to the world by inviting a deeper understanding of ourselves in
relationship with it” (Dirkx, p. 64).
15
Message design must also take learners’ cultural contexts into
consideration. People from low-context cultures assign less meaning to
context but focus on the message itself. Thus, low-context cultures use
language with great precision and economy; high-context cultures use
language lavishly because words have relatively less value. High-context
cultures might involve implicit context; whereas low-context cultures need
explicit context (Hall & Hall, 1990).
21. ACTIVITY DESIGN: INTERACTIVE, COLLABORATIVE
OR SOLO AND COMPETITIVE
Activity design should accommodate learners’ needs and learning styles.
The ultimate goal is to help learners bond and thus build a network in which
they can work comfortably. Activities could come in various formats:
interactive, cooperative and collaborative, or solo and competitive.
Collaborative learning increases student satisfaction with the learning
process (Jung, Choi, Lim, & Leem, 2002). Ample research has shown that
the collaborative group experienced heightened satisfaction, which is a
precursor for continued student involvement with any given delivery
method.
Technological advances are making collaborative online learning more
feasible. Along with a greater focus on increasing social presence, this
enhanced feasibility in turn increases the ease of building online
communities. Collaborative learning, when used wisely, could facilitate
learning to a greater extent than individual learning. Exemplary wise uses
include:
a. Structured group assignments requiring project outcomes that
incorporate e-mail, chat, conferencing, and message boards
appropriate to the degree of concurrency in the learning
environment.
b. Structured study assignments for pairs of learners that use
various communication tools such as chat and e-mail.
c. Knowledge management facilities that extend learning through
discussion boards or social software (Clark & Mayer, 2003).
On the other hand, certain constraints could potentially limit the
effectiveness of collaborative learning. For example, an over-sized team,
mechanically assigning students to a group but failing to provide guidance,
and assessing students individually when they are engaged in teamwork.
In addition, despite the great benefits of collaboration in online learning,
some learners work best solo or competitively. Thus, instructors should
16
encourage collaborative learning but also allow students to choose the mode
of work and learning that suits their learning style.
Effective instruction requires the instructor to step outside the realm of
personal experiences and into the world of the learner, who must be engaged
for learning to occur (Brown, 197). In addition, learning must be
individually constructed to be meaningful (Newmann et al. in Brown, 1997).
By varying course delivery methods and providing students with a range of
options, the instructor gives students autonomy and flexibility in their own
learning (Brown).
22. CULTIVATING A BETTER SENSE OF SELF
This first thing an instructor needs to do is to increase learners’ self-
confidence, competence, efficacy with technology tools. To help students
build a positive sense of an online self, instructors should always start with
what students already know and show them the continuity of learning.
Instructors should also encourage students to act upon growing their self-
efficacy (Kiger, 2001), with not only the learning tasks but online
communications and technological tools.
23. DETECTING STUDENTS’ EMOTIONAL CUES ONLINE
Accurately identifying a learner’s cognitive-emotive state greatly
enhances an instructor’s ability to help learners take pleasure in the learning
process (Kort et al.). In online communication, emotional cues are solely
represented in texts on screens. Because of the lack of facial expressions,
body language, and the content and tone of speech, instructors need to
remain more alert during synchronous interactions such as live chat. Do a
few students dominate the conversation? Do other students log on but
refrain from participation, playing the role of “lurkers”? What emoticons are
students using? Although some discourage using emoticons in professional
email communications, the wide array of emoticons could vividly convey
students’ feelings and emotions in online discussions.
Emoticons are pictographs of facial expressions made by a certain series
of keystrokes. Following are the most commonly used ones in online
learning situations (http://www.computeruser.com/resources/dictionary/
emoticons.html):
: ( Sad
: ) Smile
: [ Bored, sad
#:-o Shocked
17
%-( Confused
%-) Dazed or silly
%-6 Brain-dead
%-{ Ironic
%-| Worked all night
%-} Humorous or ironic
>>:-<< Furious
>:-< Angry
(:-\ Very sad
/\/\/\ Laughter
12x@>--->--- A dozen roses
:-| Indifferent, bored or disgusted
Instructors could distribute an emoticon sheet at the beginning and ask
students to use it to candidly express their emotions. However, learner
emotions are more reflected in their non-emoticon interactions. Thus,
instructors should also analyze the content of the online discussions to detect
the emerging emotions. Although systematic content analysis (Fraenkel &
Wallen, 2003) can be a complex process, instructors could build a transcript
analysis scheme (see Table 2 as follows) and use a fast coding approach
(Chappel, 2002) to quickly determine the interaction patterns. Table 2 below
tabulates the emotions commonly felt by students in online learning.
Table 2. A sample transcript analysis scheme (adapted from Kort et al.)
Anxiety-
Confidence
Anxiety Worry Discomfort Comfort Hopeful Confident
Boredom-
Fascination
Ennui Boredom Indifference Interest Curiosity Intrigue
Frustration-
Euphoria
Frustrati
on
Puzzled Confusion Insight Enlighten
ed
Ephipany
Dispirited-
Encouraged
Dispirite
d
Disappoin
ted
Dissatisfied Satisfied Thrilled Enthusiast
ic
18
Fear-
Enchanted
Apprehe
nsion
Embarras
sment
Frustration Calm Anticipat
ory
Excited
The fast coding approach that Chappel and her colleagues suggest can be
used to characterize contextualized online learning behaviors as an
interpretative aid for tutors and instructors working in online learning
environments. In fast coding, coders pre-determine the elements, such as the
categories in a coding scheme, and purposively look for these elements in
communication evidence. Accordingly, instructors could use a customized
Transcript Analysis Scheme and fast coding approach to identify the
aforementioned emotions revealed in online discussions.
24. FACILITATING ONLINE COMMUNICATION
Communication skills for effective online teaching are twofold: the
ability to transmit messages clearly and accurately, and the ability to
maintain positive interpersonal relationships (White & Weight, 1999).
Ineffective communication has been found to be the major cause of the
fragmentation of a learning community, which then leads to feelings of
isolation and confusion. The National Teaching and Learning Forum
Newsletter suggests guidelines to foster online discussion and collaborative
learning, including the following:
a. clearly state the purpose of online discussion
b. help students be metacognitively aware of their learning styles
and approaches
c. establish a style of writing and convention
d. link online discussion to assessment
e. use concise and clear language; keeping the posts short and right
to the point
f. provide feedback to all participants to summarize the discussion,
refer students to further reading, and to evaluate the quality of
their contribution to the session.
White and Weight suggest the following methods to successfully build
and maintain the positive learning environment. First, an instructor needs to
be warm, responsive, inquisitive, tentative, and empathetic when
communicating with students. This can be achieved by using appropriate
tones (firm, fair, flexible, & fun) and nonjudgmental, non-dogmatic phrases
like “it seems that… it appears that… I think”). Second, an instructor needs
to model communication netiquette, such as to enhance class visibility by
19
sending public messages, to keep posts brief and to the point, to keep the
discussions on topic, and to cite relevant messages while responding.
Third, an instructor should also model constructive reactions to technical
difficulties. Finally, an instructor should provide appropriate feedback to
students’ work—to give feedback and grades on a timely and regular
schedule and to treat students as unique individuals.
25. BUILDING LEARNING COMMUNITIES
Meaningful interaction and collaborative teamwork are the natural ways
of building online communities. Various types of online interaction include
acknowledgement, agreement, apology, self-criticism, questions, humor,
invitation, and referential statement; however, debates, open negotiation, and
constructive argumentation are the most effective means of strengthening
social ties among a group of learners and thus contribute most strongly to
building the community (Wang, Folger, & Sierra, 2003). In addition,
argumentation and consensus-reaching are the venues for constructing
shared knowledge or a knowledge artifact; this artifact can then be
continuously referred to and used to support other arguments (Stahl, 1999).
Online relationships can be more intimate and intense than those
maintained in face-to-face settings (Anderson & Park, 1994). The lack of
physical appearance in online communication in fact facilitates self-
disclosure without taking risks. This anonymous mode of communication
“serves as a springboard for formation of intensive, pleasurable, deep, and
rich interpersonal connections. In addition, it offers the possibility to enter
into simultaneous relationships with a number of people” (Schnarch in Oren
et al., Introduction, ¶ 5).
Therefore, online instructors should intentionally encourage candid and
uninhibited communication, so as to build a foundation for meaningful
negotiation. They should establish a netiquette from the beginning of the
course, encouraging students to freely express opinions and thoughts that
differ from those of others including those of the instructor. Instructors must
also attend to individuals who have trouble crossing the “threshold” of a
community (Wegerif). In addition, communication will flow freely in these
communities only if information is free of personal agendas, power
struggles, and hidden prejudices (Stahl). If these negative elements can be
avoided and true sharing of ideas becomes the norm, then new knowledge
can be created.
Small-team collaboration monitored by an instructor is necessary for an
online class to establish social relationships and the sense of community.
Collaborative learning strategies help to maintain the sense of community
and are crucial for creating positive learning outcomes for students (Hiltz,
20
1998; Wang, Sierra, & Folger, 2003). Online course design should maintain
a good balance between independent and team tasks. The learning tasks
should allow individuals to extend their creativity and should use teamwork
as a safety net to prevent individuals from suffering “crash-and-burn.” The
goal is one of creating a balance between community-building and legitimate
peripheral learning, where students participate at a distance and eventually
become part of a community (Wegerif).
On the other hand, instructors must also respect individual differences
and allow witness learners to develop. Some adults take online courses in
part because the “socialization” aspect of the experience is secondary to the
grade/qualification received (Wang & Aurilio, 2003). In particular, older
adults with families might have firmly established their social network and
thus have less desire to form a “cyber” network. In these cases, instructors
should take the initiative to reach out to witness learners to ensure that they
are still engaged in the learning tasks even though remaining outside the
community or as “witness learners”.
Instructors should tactfully encourage social discussions but then lead the
discussions toward course content. Following are some strategies that would
increase social interaction in an online community:
a. Support a healthy group dynamic: encourage collaborative team-
work as a powerful configuration for the accomplishment of
learning tasks.
b. Moderate group work in a way that enables students to interact,
for example by creating a group space in online course
management system;
c. Encourage participants to abide by the netiquette
d. Use supportive feedback to enhance the social atmosphere
e. Create a social forum as a designated place for social integration
of the learning group. (Oren et al., Implications, ¶ 3)
How do we know if community is built? Although community is specific
to setting (Rovai, 2001), online communities share common attributes such
as spirit (feeling of group identity), trust (feeling of safety and support),
interaction (dynamics), and learning (construction of shared knowledge)
(Wang & Poole, 2004).
26. USING SOCIAL SOFTWARE TO DEEPEN THE SHARING
OF PERSONAL CONCERNS AND EMOTIONS
A variety of online tools can be used to facilitate online communication
and community-building: asynchronous discussion groups and conferences,
21
synchronous chats, live audio and video webcasts, informal virtual meeting
spaces, and social software such as Blog, Wiki, or Moodle.
Social software refers to the several emerging CMC tools and open-
source web-authoring tools such as Blogs, Wikis, Moodle, or other
collaboration systems, shared spaces, and any virtual world where people
interact, as well as related tools and data structure for identity, integration,
interchange, and analysis (Social Software Alliance, 2004). Social software
supports easy personal publishing on the Internet without knowing authoring
codes (html). Thus, it frees people from technical details and allows them to
focus on creating and publishing knowledge with a few mouse clicks.
Social software encompasses support for one or more of the following
elements: a) conversational interaction between people or groups, b) social
feedback, and c) social networks (Boyd in Kaplan-Leiserson, 2003). Also,
social software enables people to organize themselves into a network based
on their preferences. Its strong support for social networks encourages the
establishment of an immediate online community. Thus, social software
represents a new form of communication and community-building that
eliminates the need for geographic proximity and face-to-face meetings. In
addition, authoring tools like Wikis provide a collaborative workspace for
collective work.
Social software puts learners at the center of their educational experience
and positions them as active stakeholders who are better motivated to learn
(Pierce & Kalkman, 2003; Ferdig & Trammell). Knowing that a larger
audience is reading her published work could increase a learner’s
accountability and desire to produce a quality product. The sense of writing
to a larger audience in a global medium can be very motivating. Oravec
(2002) contends that social software, such as blogs, also empowers all
students by making their voices heard online regardless of their performance
in face-to-face meetings.
Social software has not been widely used in teaching and learning, and
thus research is still limited. Anecdotal evidence has shown that social
software has the unique effect of spurring online interaction, which is the
foundation for cognitive, teaching, and social presence. The student is
cognitively present through frequent interaction with the material,
experiences teaching presence through effective interaction with the
instructor, and enjoys social presence through interaction with other students
(Hutchins, 2003).
22
27. ENGAGING STUDENTS OF DIVERSE LINGUISTIC AND
CULTURAL BACKGROUNDS
The diverse cultural contexts of online learners have great implications
on their engagement in the learning process. Engaging students emotionally
is especially critical for learning environments that involve multi-cultural
students distributed around the world.
Engagement is positively correlated with motivation, which may be
prompted in different ways for culturally different students (Wlodkowski &
Ginsberg, 1995). Wlodkowski and Ginsberg consider engagement the visible
outcome of motivation. Emotions influence motivation, and emotional
responses are partly a product of culture. To engage students effectively, an
instructor must know students’ cultural background and perspectives and be
able to see them as unique and active.
Wlodkowski (2003) proposes a Motivational Framework for Culturally
Responsive Teaching, which can be used to foster better participation and
learning by students from diverse cultures. The framework synergizes
individual cultures to create a common culture in the learning situation that
can be accepted by adult learners. Thus, this framework is exemplary in
integrating strategies that address all four factors in the emotive domain:
feelings of self, feeling of community, feelings of learning atmosphere, and
feelings emerging from the learning process.
There are four motivational conditions that the instructor and the learners
collaboratively create. First, cultivating learners’ competence about being
effective in learning valuable things; second, creating a respectful and
connected learning atmosphere; third, helping learners develop favorable
attitudes toward the learning experience through personal relevance and
choice; and fourth, creating challenging and thoughtful learning experiences
that are consistent with learners’ perspectives and values.
28. CONCLUSION
For teaching to be effective, cognitive, emotive, and social factors must
work together. For online learning experience to be successful, students must
have sufficient prior knowledge, be motivated to learn, and be positively
engaged in the learning process. In addition, they must also be comfortable
with the learning environment and feel a strong sense of community and
social commitment. Finally, emotive factors heavily affect students’
engagement in the learning. Thus, instructors must be sensitive to students’
emotional state and must take initiative to channel students’ emotions to the
23
good “zones,” such as the zone of curiosity, zone of flow, and zone to a
productive path.
The Cybergogy for Engaged Learning model that we propose can be used
to conduct needs assessment and to lay out course design and facilitation
techniques. Instructors could use this model to profile each student’s
cognitive, emotive and social attributes and then effectively engage learners
by addressing individual’s learning needs and attributes. The model can be
used to enhance learners’ cognitive, emotive and social presence,
Our Model for Engaged Learning reflects the systemic approach to online
learning. Here, online learning is viewed as an entity designed to incorporate
input from the learning environment, transform the input into output,
distribute that output into the environment, and make adjustments as
necessary to the changing conditions of the environment. The key features of
this systemic view include: a) putting the right people, elements and
resources in place to succeed; b) evaluating results through learning
outcomes; and c) providing feedback and taking action to maintain
alignment with established educational and societal goals. Factors in the
cognitive, emotive, and social domains are identified as critical elements in a
learning environment when used as input in the system described. These
input elements together transform the learning system into cognitive,
emotive, and social presence, and they finally generate engaged learning as a
whole.
However, this model is still theoretical and therefore needs to be
validated through systematic studies of diverse online classes. In addition,
our model does not include the newly emerged notion of “transactional
presence”, which addresses online students’ perceptions of psychological
presence/availability of and their connectedness with teachers, peers, and
institutions in distance education environments (Shih, 2003). We plan to
further develop this model through empirical research and through
integrating constructs from this transactional presence theory.
24
REFERENCES
Arnone, M. P. (2003). Instructional design strategies to foster curiosity, from
http://www.ericit.org/digests/EDO-IR-2003-01.shtml
Bandura, A., & Cervone, D. (1986). Differential engagement of self-reactive
influences in cognitive motivation. Organizational Behavior and Human
Decision Processes, 38, 92-113.
Bangert-Drowns, R. L., & Pyke, C. (2001). A taxonomy of student
engagement with educational software: An exploration of literate
thinking with electronic text. Journal of Educational Computing
Research, 24(3), 213-234.
Bangert-Drowns, R. L., & Pyke, C. (2002). Teacher ratings of student
engagement with educational software: An exploratory study.
Educational Technology Research and Development, 50(2).
Brown, B. L. (1997). New learning strategies for Generation X [Electronic
version], 184, from Retrieved from Eric Database.
Carrier, S. I., & Moulds, L. D. (November 2003). Pedagogy, andragogy, and
cybergogy: exploring best-practice paradigm for online teaching and
learning. Paper presented at the the 9th Annual Sloan-C/ALN
(Asynchronous Learning Networks) Conference, Orlando, Florida.
Currin, L. (12/16/2003). Feelin' groovy. Elearn Magazine. Retrieved March
22, 2004 from http://elearnmag.org/subpage/sub_page.cfm?article_pk=
10221&page_number_nb=1&title=FEATURE%20STORY
Dirkx, J. (Spring 2001). The power of feelings: Emotion, imagination, and
the construction of meaning in adult learning. New Directions for Adult
and Continuing Education, 89, 63-72.
Driscoll, M. P. (2002). How people learn (and what technology might have
to do with it) [Electronic version]. ERIC Digest, 1-4.
Dweck, C.S., & Leggett, E.L. (1988). A social-cognitive approach to
motivation and personality. Psychological Review, 95, 256-273.
Eppler, M.A., & Harju, B.J. (1997). Achievement motivation goals in
relation to academic performance in traditional and non-traditional
college students. Research in Higher Education, 38, 557-573.
Foegen, A., & Hargrave, C. P. (Winter 1999). Group response technology in
lecture-based instruction: exploring student engagement and instructor
perceptions. Journal of Special Education Technology [Online]. 14(1),
3-17.
Garrison, D. R., & Archer, W. (2000). A transactional perspective on
teaching and learning: A framework for adult and higher education.
Oxford, UK: Pergamon.
Hall, E. T., & Hall, M. R. (1990). Understanding cultural differences.
Yarmouth, Me.: Intercultural Press.
25
Hannafin, M. et al. (2003). Cognitive and learning factors in web-based
distance learning environment. In Moore, M. & Anderson, W. (Eds.).
Handbook of distance education. Lawrence Erlbaum Assoc. Mahwah,
New Jersey.
Hara, N., & Kling, R. (2000). Students’ distress with a Web-based distance
education course: An ethnographic study of participants’ experiences.
Center for Social Informatics, Indiana University, Working paper.
Heyman, G.D., & Dweck, C.S. (1992). Achievement goals and intrinsic
motivation: their relation and their role in adaptive motivation.
Motivation and Emotion, 16, 231-237.
Hill, J. R., Wiley, D., Nelson, L. M., & Han, S. (1996). Exploring research
on internet-based learning: from infrastructure to interactions. In D.
Jonassen (Ed.), Handbook of research for educational communications
and technology (pp.433-449). New York: Simon and Schuster.
Hiltz, S. R. (November 7-12, 1998). Collaborative Learning in
Asynchronous Learning Networks: Building Learning Communities.
Paper presented at the WebNet 98 World Conference of the WWW,
Internet, and Intranet Proceedings, 3rd, Orlando, FL.
Hoyert, M. S.,& O'DelI,C.D. (2000a). Goal orientation in traditional and
non-traditional aged college students. Manuscript submitted for
publication.
Hoyert, M.S., & O'Dell, C.D. (2000b). Goal orientation and response to
failure in a challenging college course. Manuscript submitted for
publication.
Hutchins, H. M. (Fall 2003) Instructional Immediacy and the Seven
Principles: Strategies for Facilitating Online Courses. Retrieved March,
6, 2004 from http://www.westga.edu/~distance/ojdla/fall63/hutchins63
.html
Jones, B. F., Valdez, G., Nowakowski, J., & Rasumssen, C. (1995). Plugging
In: Choosing and Using Educational Technology: Council for
Educational Development and Research, the North Central Regional
Education Laboratory (NCREL).
Kaplan-Leiserson, E. (December 2003). We-Learning: Social Software and
E-Learning, from
http://www.learningcircuits.org/2003/dec2003/Kaplan .htm
Katz, Y. (2002). Attitudes affecting college students’ preferences for distance
learning [Electronic version]. Journal of Computer Assisted Learning,
18, 2-9.
Keller, J. M., & Suzuki, K. (1988). Use of the ARCS motivation model in
courseware design. In D. H. Jonassen (Ed.). Instructional designs for
microcomputer courseware. Hillsdale, NJ: Lawrence Erlbaum.
26
Kiger, P. J. (March, 2001). At First USA bank, promotions and job
satisfaction are up. Workforce, 54-56.
Kort, B., Reilly, R., & Picard, R. (2001). External representation of learning
process and domain knowledge: Affective state as a determinate of its
structure and function, retrieved February 14, 2004 from
http://affect.media.mit.edu/AC_research/lc/AI-ED.html
LaViolette, P. A. (1979). Thoughts about thoughts about thoughts: The
emotional-perceptive cycle theory. Man-Environment Systems, 9, 15-47.
LaViolette, Paul A. Teaching with Feeling in Mind. Reprinted from On the
Beam, 6(2) (1986). Retrieved Jan 12, 2003 from http://www.etheric
.com/LaViolette/Feel-ingtones.html
Locke, E. A., Frederick, E., Lee, C., & Bobko, P. (1984). Effects of self-
efficacy, goals and task strategies on task performance. Journal of
Applied Psychology, 69, 241-251.
Lumpe, A. T., & Chambers, E. (Fall 2001). Assessing teachers' context
beliefs about technology use. Journal of Research on Technology in
Education. Retrieved from the WilsonWeb datase, 34(1), 93-107.
Magna Publications, I. (April 2002). Understanding Student Frustration.
Online Classroom. Retrieved from the WilsonWeb database, 1-2.
McLeod, S. H. (1991). The Affective Domain and the Writing Process:
Working Definitions. Retrieved February 4, 2004 from
http://jac.gsu.edu /jac/11.1/Articles/6.htm
Merrill, D. (2002). First principals of instruction. Educational Technology
Research and Development, 50(3), 43-59.
O'Regan, K. (September 2003). Emotion and E-learning. Journal of
Asynchronous Learning Networks, 7(3), 78-92.
Oren, A., Mioduser, D., & Nachmias, R. (April - 2002). The Development of
Social Climate in Virtual Learning Discussion Groups, from
http://www.irrodl.org/content/v3.1/mioduser.html
Reis, R. (2003). Tomorrow's Professor Msg.#342 Teaching for Engagement,
from http://sll.stanford.edu/projects/tomprof/newtomprof/postings/342.
html
Riding, R. J., & Rayner, S. (1998). Cognitive styles and learning strategies:
understanding style differences in learning and behaviour. London:
David Fulton Publishers.
Roedel, T.D., Shraw, G., & Plake, B.S. (1994). Validation of a measure of
learning and performance goal orientations. Educational and
Psychological Measurement. 54, 1013-1021.
Schunk, D. H. (1990). Goal setting and self-efficacy during self-regulated
learning. Educational Psychologist, 25, 71-86.
Shih, N. (2003). Transactional presence as a critical predictor of success in
distance learning. Distance Education, 24(1), 69-86.
27
Simon, G. (2002). E-tivities: The key to active online learning. London:
Kogan Page Ltd.
Snell, J. C. (2000). Teaching generation X & Y: An essay part 2: Teaching
strategies [Electronic version]. College Student Journal, 34(4), 482-484.
Social Software Alliance, S. S. (2004). Alliance Charter, from
http://www.socialtext.net/ssa/index.cgi?Alliance%20Charter
Stahl, G. (1999). Perspectives on collaborative knowledge-building
environment: Toward a cognitive theory of computer support for
learning. Retrieved December 10, 2001 from http://orgwis.gmd.de/
~gerry/publications/conferences/1999/csc199/kbd_workshop/kbe_theory
1.pdf
Wang, M. J. (2000). The Construction Of Shared Knowledge In An Internet-
Based Shared Environment For Expeditions (iExpeditions): A Study Of
External Factors Implying Knowledge Construction. Unpublished
doctoral dissertation, University of Missouri, Columbia.
Wang, M. J., & Poole, M. (2004). Nurturing a dynamic online learning
community among teens. In M. Kalantzis & B. Cope (Eds.), The
International Journal of Learning, 9. Melbourne, Australia: the
University Press/Common Ground. [Online]. Retrieved December 1,
2004 from http://LC2002. Publisher-Site.com/ProductShop/
Wang, M. J. & Aurilio, S. (2004). Does socializing enhance learning
outcomes in online settings? Paper to be presented at Ed-Media 2004
conference, Lugano, Switzerland, June 21-26, 2004.
Wang, M. J., Sierra C., & Folger, T. (2003). Building a dynamic online
learning community among adult learners. Educational Media
International (Special Issue: computer-mediated communication),
40(1/2), 49-61.
Wegerif, R. (March 1998). The Social Dimension of Asynchronous Learning
Networks. Journal of Asynchronous Learning Networks, 2(1), ??
Weiss, R. P. (2000, November). Emotion and learning [Electronic version].
Training and Development, 54, 44-48. Retrieved February 10, 2004,
from EBSCO Host research database.
White, W. & Weight, H. (2000). Online teaching guide: A handbook of
attitudes, strategies, and techniques for the virtual classroom. Needham
Heights, Massachusetts: Allyn & Bacon.
Wlodkowski, R. J. (Summer 2003). Fostering Motivation in Professional
Development Programs. New Directions for Adult and Continuing
Education(98), 39-47. Retrieved from WilsonWeb.
Wlodkowski, R. J., & Ginsberg, M. B. (Sep 1995). A framework for
culturally responsive teaching. Educational Leadership Alexandria,
53(1), 17-. Retrieved from ProQuest.
Vygotsky, L. S. (1986). Thought and language. Cambridge: MIT Press.
28
Appendix A
Table 1. A Taxonomy of Forms of Engagement and Assessment Strategies
Critical Factors for
Engaged Learning
Indicators of
Engaged
Learning
Methods of
Assessment
Cognitive:
•Prior knowledge/experience:
•familiar, unfamiliar
•Achievement goal:
•learning, performance
•Learning activity: well-
structured,
•ill-structured
•Cognitive/learning style
Cognitive
engagement:
•Self-regulated
learning
•Ownership of
learning
•Generative
learning
•Knowledge
construction
•Discourse
analysis
•Observation of
learning process
•Performance
analysis
•Survey of
students’ self-
perception
Emotive:
•Feelings of self: confidence
•competence, efficacy
•Feelings of community
•Feelings of learning
atmosphere: safe and positive
versus fearful; open negotiation
versus domination
•Feelings of the learning process:
interest/curiosity,
confusion/anxiety/frustration,
fascination or boredom, pride,
satisfaction or dissatisfaction
Emotional
engagement:
•Feeling
confident
•Feeling secure
•Feeling
comfortable
•Feeling
curious
•Discourse
analysis of
communication
evidence for
emotional cues and
words
•Survey on
student perceptions
Social:
•Personal attributes: age and
gender, language and media
literacy abilities
•Learner’s social-cultural
context: goals, motives,
expectations, and value, group
size, discussion content,
necessary software, and group
moderation
•Community-building, marked
by group identity, trust,
Social engagement:
•Sharing
resources and
information
•Cohesiveness
•Acceptance
•Collaborative
learning
•Discourse analysis
•Observation of live
discussions
•Community-
forming: group
identity, trust,
interaction, and
construction of
shared knowledge
29
interaction, and construction of
shared knowledge
•Communication skill: student,
instructor, moderator
30