होम Group Decision and Negotiation Role-Based Experiences, Media Perceptions, and Knowledge Transfer Success in Virtual Dyads

Role-Based Experiences, Media Perceptions, and Knowledge Transfer Success in Virtual Dyads

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DOI:
10.1007/s10726-006-9047-5
Date:
July, 2006
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आप पुस्तक समीक्षा लिख सकते हैं और अपना अनुभव साझा कर सकते हैं. पढ़ूी हुई पुस्तकों के बारे में आपकी राय जानने में अन्य पाठकों को दिलचस्पी होगी. भले ही आपको किताब पसंद हो या न हो, अगर आप इसके बारे में ईमानदारी से और विस्तार से बताएँगे, तो लोग अपने लिए नई रुचिकर पुस्तकें खोज पाएँगे.
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Supporting Technologies and Organizational Practices for the Transfer of Knowledge in Virtual Environments

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2

Strengthening Identification with the Team in Virtual Teams: The Leaders' Perspective

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2006
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english
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PDF, 201 KB
Group Decision and Negotiation 15: 367–387, 2006.
DOI: 10.1007/s10726-006-9047-5


C Springer 2006

Role-Based Experiences, Media Perceptions,
and Knowledge Transfer Success in Virtual Dyads∗
BRYAN K. HASTY
Information Systems Department, Indiana University, 1309 E. 10th Street BU560, Bloomington, IN 47405
(E-mail: bhasty@indiana.edu)

ANNE P. MASSEY
Information Systems Department, Indiana University
(E-mail: amassey@indiana.edu)

SUSAN A. BROWN
Management Information Systems Department, University of Arizona
(E-mail: suebrown@eller.arizona.edu

Abstract
Knowledge transfer (KT) is the process through which one is affected by the experience of another. While many
of the challenges of KT have been discussed in the literature (e.g., incentives, cognitive limitations), the challenge
of KT in virtual settings has received limited attention. In this paper, our interest lies in exploring asymmetric
KT where a sender has more knowledge about a topic than a receiver. We focus on a dyadic relationship between
geographically dispersed sender and receiver units, supported by a multi-media technology environment. Drawing
from the KT literature and Channel Expansion Theory, we specifically explore the evolution of and relationship
between role-based experiences (e.g., with partner, topic, media) and media richness perceptions. Our results
provide evidence that KT roles do matter relative to the acquisition of experiences and expansions in media
richness perceptions. Despite some differences in acquired experiences, our results also suggest that KT partners
converge in their perceptions of acquired experiences and evolve to shared (or congruent) perceptions of media
richness. Finally, our results provide evidence that sender-receiver congruence in media richness perceptions
influences KT success.
Key words: knowledge transfer, virtual work, channel expansion theory, multi-media, media richness

1. Introduction
By enabling new ways of distributing work, technological advances have given rise to
“virtual” work (Boudreau et;  al. 1998; Jarvenpaa and Leidner 1998). Virtual work consists
of geographically dispersed individuals who communicate and collaborate via electronic
media to accomplish tasks. While many of the challenges of knowledge transfer (KT) have
been discussed in the literature (e.g., incentives, cognitive limitations) (Szulanski 2000; Ko
et al. 2005), the challenge of KT in distributed settings has received limited attention.

∗

All correspondence regarding this paper may be directed to Bryan Hasty.

368

HASTY ET AL.

KT is the process through which one unit is affected by the experience of another unit
(Argote and Ingram 2000). KT occurs by moving a knowledge reservoir from a sender
to a receiver with transfer manifested through changes in understanding of the recipient.
Argote and Ingram (2000) suggest that ascertaining how knowledge understanding changes
as a function of experience (e.g., with a KT partner) is an important undertaking. In a
virtual setting, however, since partners rely on electronic media to affect KT, we must also
consider how knowledge understanding changes as a function of media experience and
media perceptions.
Any given media is comprised of characteristics such as richness and interactivity (Zack
1993; Boland et al. 1994; Dennis and Valacich 1999). Media richness and interactivity are
highly developed, well-studied constructs that are significantly interrelated (Fulk and Boyd
1991; Zack 1993; Webster and Trevino 1995). Daft and colleagues defined richness as a
blend of four factors: (1) the immediacy of feedback, (2) the use of multiple cues (verbal
and non-verbal), (3) language variety, and (4) the ability to personalize messages (Daft
et al. 1987). In KT, a sender must work to articulate knowledge and simultaneously reduce
equivocality on the part of the receiver. Media allowing for rapid feedback, multiple cues
and language variety (e.g., graphics) helps to reduce equivocality, and thus, should enable
KT.
While media can enable KT, several studies suggest that, in actual use, media can be
perceived differently – or acquire different meanings – by senders and receivers (Orlikowski
and Gash 1994; Karsten 1995). This may be particularly true in virtual settings wherein
participants rely heavily (if not entirely) on electronic media to communicate, may have
little (if any) history of working together using various media, and may be separated not only
geographically, but also culturally. For example, Massey et al. (2002) found that different
national cultures perceive media differently. Moreover, experience with topic, partner, and
media have been demonstrated to impact media perceptions – leading to an evolving view
of richness (Carlson and Zmud 1999). It seems possible that the experiences of senders and
receivers may evolve in different ways, leading to differing perceptions of media richness.
Incongruence in media perceptions may negatively affect the KT process and its outcomes
(Kock 2004).
In this paper, we examine role-based (sender and receiver) experiences and media perceptions in an experimental setting involving a KT task. Our first research question centers
on examining whether (or not) KT roles matter in the acquisition of experiences and the
evolution of media richness perceptions over time. The sender-receiver dyads in our experiment are geographically dispersed and communicate solely via electronic media. Whereas
past research has largely focused on the use of one media at a time, our participants have
access to three media that they may use either singularly or in concert. Importantly, past
research (Barley 1986; Markus 1994) suggests that KT partners will develop shared beliefs
about what a medium is good for in the process of using it. As such, our second question
centers on examining whether or not (in)congruence in media richness perceptions by KT
partners affects the success of KT, where success is defined as an increase in understanding
on the part of the receiver. In order to address our research questions, we establish an asymmetric KT context where the sender has more knowledge about a topic than the receiver.
This structure is widely observed in practice, e.g., technology transfer (Argote 1999; Argote

ROLE-BASED EXPERIENCES, MEDIA PERCEPTIONS

369

et al. 2000), new product development (Massey et al. 2002), and distance education (Griffith
and Neale 2001), and thus has significant practical importance.
In the next section, we describe the theoretical background and offer our research hypotheses. Then, we describe the methodology of our experimental design and analytic
approach. Finally, we discuss our results and offer directions for future research.

2. Theoretical Background and Hypotheses
Arguably, one of the most important aspects of collaborative work is the transfer of knowledge from one set of individuals to another (Nonaka 1994). KT can occur among entities
spanning multiple levels, i.e., among individuals, groups, and organizations (Inkpen and
Dinur 1998; Argote and Ingram 2000). In order for knowledge to be useful for others,
senders must express it in such a manner as to be interpretable by the intended receivers
(Alavi and Leidner 2001). Receivers must “decode” the symbols that constitute a message
and interpret the meaning of the sender. For communication to be successful, both the sender
and receiver must mutually agree that the receiver has understood the message (Clark and
Wilkes-Gibbs 1986). Feedback from the receiver to the sender plays an important role in
communicating to the sender that the receiver has understood the message (Dennis and
Kinney 1998).
With the increase in globalization, KT increasingly occurs among entities that are not
necessarily co-located, but separated by geographic distances (Nonaka 1994; et al. 2001).
The contexts within which senders and receivers encode and interpret information are likely
to differ significantly when their geographic locations are distant, increasing the likelihood
of misinterpretation (Cramton 2001). To date, researchers have attempted to investigate KT
at individual (Empson 2001), group (Szulanski 1996), and organizational levels (Zander and
Kogut 1995; Mowery et al. 1996), although with very few exceptions, such investigations
have been limited to co-located organizational members (Sarker et al. 2005). Szulanski
(2000) suggests that “knowledge transfers are often laborious, time consuming, and difficult” (p. 10) and argues that it is important to examine the process of KT to be able to
produce more favorable outcomes. Given these difficulties, it is reasonable to expect that KT
may become even more problematic in virtual situations where participants communicate
via technology.
Computer-mediated communication has been examined from a variety of views, perhaps
the most prevalent of which is Media Richness Theory (MRT) (Daft and Lengel 1984; Daft
and Lengel 1986). While MRT offers individual-level rational choice explanations of behavior, in reality, KT is not a static process (Massey and Montoya-Weiss 2006). Specifically,
the evolving nature of partner relationships, while critical to communication and KT, is not
explicitly considered in MRT (Markus and Keil 1994). Other factors, such as evolving experience with various media and the topic itself, are also not considered. Channel Expansion
Theory (CET) (Carlson and Zmud 1994; Carlson and Zmud 1999) extends the findings of
MRT beyond its original prescriptive structure to examine how media richness perceptions
expand over time. This “expansion” is the heightening of one’s perception of the richness
of a media through the acquisition of various experiences. Specifically, Carlson and Zmud

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(1999) propose that an individual’s perception of a media’s richness is based on experiences
with: (1) the media, (2) a communication partner, (3) the topic, and (4) the organizational
context. In their initial study involving email, Carlson and Zmud (1994) report that acquired
experiences with the media, partner, topic, and organizational context were all found to be
significant indicators of perceived media richness and subsequent expansion. In a follow-up
study, Carlson and Zmud (1999) found that experience with the message topic was not
significant.
CET does not, however, directly address the possible influence of role behaviors on
perceptions of experiences and media richness. Related social-temporal theories similarly
do not account for the potential influence of roles. For example, the symbolic interactionist
perspective suggests that there would be no difference between senders and receivers in
media preferences (Russ et al. 1990). However, in contrast to what the symbolic interactionist
perspective suggests, an individual might select a particular medium to send a message,
but prefer to receive that same message through a different medium (Russ et al. 1990).
For example, senders may feel a greater need than receivers to ensure that a message is
understood and thus prefer media perceived to be richer. In an asymmetric KT context,
the parties involved have specific role behaviors as senders (sources) of knowledge and
receivers (recipients) of knowledge. Thus, while both parties will likely perceive acquisition
in experiences and expansion in media richness as stated above, we propose that it is
likely that role-related issues may lead to differences in both areas. For example, given the
asymmetric context, it is likely receivers will acquire greater topic experience than senders
who are responsible for transferring topic-related knowledge. With less attention paid to
further acquisition of topic experience, senders may focus more attention on ascertaining
the evolving knowledge of their partner, thus increasing acquisition of partner experience.
While we offer no a priori prediction regarding which partner will acquire more media
experience, we do expect that when and how various media are used will likely lead to
role-based differences in perceptions of acquired media experiences. Consistent with CET,
we expect that differences in the acquisition of various experiences will lead to differences
in media richness perceptions. Based on this, we offer the following hypotheses regarding
experiences and richness perceptions:
H1a: In an asymmetric KT context, senders and receivers will both acquire experiences (i.e., partner, topic, and
media) over time.
H1b: In an asymmetric KT context, senders and receivers will vary in the acquisition of experiences.
H2a: In an asymmetric KT context, senders and receivers will both expand in media richness perceptions over
time.
H2b: In an asymmetric KT context, senders and receivers will vary in media richness perceptions.

With regard to KT success – defined as changes in knowledge understanding on the
part of the receiver – past research (c.f., Argote and Ingram 2000; Szulanski 1996) has
not examined how (in)congruence in media richness perceptions influences KT success.
This may be due to the fact that KT investigations have been largely limited to co-located

ROLE-BASED EXPERIENCES, MEDIA PERCEPTIONS

371

settings (Sarker et al. 2005). Yet, recent theorizing argues that schema alignment regarding
a communication medium, i.e., forming congruent perceptions, is an important factor in
task accomplishment (Kock 2004).
Past research (Carlson and Zmud 1994; 1999; Burke and Chidambaram 1999; Walther
1992; McGrath 1991) suggests that social and time-based factors likely influence media
choice and ultimately effectiveness – here, KT success. Importantly, social dynamic perspectives of media emphasize the collective character of media use and the social construction
(between KT participants) of media characteristics (Fulk 1993). These perspectives suggest
that KT partners should develop shared beliefs (or congruent perceptions) about what a
communication medium is good for in the process of using it (Barley 1986; Markus 1994;
Shumate and Fulk 2004). The interplay of sender/receiver KT needs as related to media
selection and use is a complex process as experiences are acquired and media perceptions
evolve over time (Massey and Montoya-Weiss 2006). Research (c.f., Szulanski 2000; Argote and Ingram 2000; Baldwin and Ford 1988) has examined how various factors (e.g.,
characteristics of individuals and knowledge itself) affect KT success. Given that KT partners in a virtual setting will largely (if not exclusively) use electronic media to affect KT,
we propose that success will be influenced by sender’s and receiver’s perceptions of media
richness. Kock (2004) argues that congruence reduces the cognitive effort required to use
media. It follows, then, that more cognitive effort can be devoted to the sending and receiving tasks, and less cognitive effort devoted to resolving misunderstandings due to media
selection. Given this, we offer the following hypothesis:
H3. In an asymmetric KT context, congruence in media richness perceptions will be positively related to KT
success.

3. Method
3.1. Task
Since learning is primarily regarded as a process of KT between a source and a recipient
(Harkema 2003), we selected a teaching/learning task for our study. As described earlier,
in an asymmetric KT context, a sender has more knowledge than the receiver and the KT
goal is to enhance the understanding of the receiver. The task for this study focused on
data modeling. The goal was for the sender to transfer knowledge of data modeling to a
receiver. Briefly, a data model is a conceptual representation of the data required to address
a particular concern. The data model includes the data objects (entities) and the associations
between data objects (relationships). The data model focuses on representing the data as
the user sees it in the “real world”. To use a common analogy, a data model is equivalent to
an architect’s building plan.
For this study, we selected entity-relationship (ER) modeling, a technique commonly
taught in business schools and used in practice. The basic constructs of the ER model are
entities, attributes and relationships. The model visually represents these concepts via the
Entity-Relationship diagram. The goal of the KT exercise was for senders to convey basic

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HASTY ET AL.

elements of ER diagramming such that receivers would be able to create an ER diagram from
a narrative description of a real world business domain situation. Further details regarding
the KT task are available from the authors.
3.2. Subjects
The subjects were 62 students randomly assigned to 31 sender-receiver dyads. All thirtyone receivers were drawn from an undergraduate information systems (IS) survey course
at a large Midwestern university. These students had little background in IS and no experience with data modeling. Twenty-five senders were enrolled in a graduate database design
course at a regional Southeastern university. The remaining six senders were drawn from
the undergraduate IS course. These individuals had taken a database design course the previous semester, and thus their knowledge of data modeling was consistent with the other
senders. All student participants were informed that they would be assigned to a dyad,
with members representing geographically dispersed universities. A post-experimental
questionnaire confirmed that each participant believed that his/her partner was at another
location.
These dyadic relationships reflect an asymmetric KT context where the senders possess knowledge concerning data modeling and how to develop Entity-Relationship (ER)
diagrams, while the receivers do not. The average age was 29.8 for senders and 21.6 for
receivers; 37% of senders and 63% of receivers were male. As an incentive, 5% of overall
course grades were based on participation in the exercise.
3.3. Technology
Communication media for this study were made available using an Internet-based integrated
R
system (Elluminate Live! 
) that includes three media: instant messaging (IM), internet
voice and shared whiteboard features. Given the task (described above), the shared whiteboard area allowed partners to draw figures, add text or pasted products, highlight and use
moving pointers. The IM feature provided a small portion of the screen for partners to send
and receive messages. The internet voice feature provided a half-duplex voice over Internet
capability. To gain access to the voice channel, subjects had to click on a “send” button. The
subject could speak through a microphone and be heard through a headset at the other end.
To release the channel, the button had to be clicked on again. Thus, only one member of the
dyad could speak at a time and the other could not interrupt until control was relinquished.
In total, the system reflects a collection of media options that provided both immediate
feedback (IM and whiteboard) and semi-immediate feedback (half-duplex voice).

3.4. Procedures
All subjects were first given a 30 minute tutorial on how to access and use the online collaborative system. Each dyad was scheduled to meet for three one-hour sessions over the

ROLE-BASED EXPERIENCES, MEDIA PERCEPTIONS

373

course of two weeks. During each session, senders and receivers could use any or all of
the three media (IM, internet voice, shared whiteboard) to facilitate KT. A basic outline of
topics to be transferred was given to the senders. Subjects were instructed to only communicate with each other during the scheduled sessions, using the media in the collaborative
system.
The goals of the first session were to get to know one another, become familiar with the
media in the online collaborative system, and start the process of transferring the basics of
data modeling. Simple ER models could be used to illustrate basic concepts. The second
session progressed to the sender transferring more intermediate concepts of data modeling
(e.g., associative entities, cardinality), again using illustrative examples. These activities
led to a takeaway modeling assignment for the receivers to complete and present during
the third session. The third (last) session involved the receivers presenting their assignment
solution, and gaining feedback, and/or additional instruction from the sender. At the end
of the three sessions, the receivers were given a data modeling assignment by their course
instructor to be handed in and evaluated.
A survey was administered prior to the first session to ascertain initial levels of experience
with the topic and the three media. Following each of the three interactive KT sessions,
subjects completed surveys regarding perceived experiences (topic, partner, and media) and
perceived media richness (i.e., IM, internet voice, and shared whiteboard). Twenty-five of
the 31 dyads met for all the sessions with 19 senders and 25 receivers completing all four
surveys.

3.5. Measures
The initial survey and three post-session surveys were based on previously validated scales,
measuring perceived experiences (the topic – data modeling, partner, and media – IM,
internet voice, shared whiteboard) and perceived richness of the three media. All of the
items used a seven-point Likert-type scale with anchoring values of 1 (strongly disagree)
and 7 (strongly agree). The scales were factor analyzed and loaded as expected, providing
evidence of discriminant validity. Each scale demonstrated acceptable reliability, with all
Cronbach alpha values greater than .80. Further, there were no increases in scale reliability
from dropping any items.
Items adapted from Carlson and Zmud (1999) provided measures for the subjects’ perceived experiences and perceived richness. Experience with the topic was measured using
a three item scale (alpha: 0.88). The experience with each of the three media (IM, internet
voice and shared whiteboard) was measured using six items (IM: alpha = 0.91; internet
voice: alpha = 0.96; shared whiteboard: alpha = 0.96). Experience with the KT partner
was measured using six items (alpha = 0.92). The perceived richness of the three media
was measured using four items each from Carlson and Zmud (1999) and an additional three
items taken from a scale developed by Dennis and Kinney (1998) for a total of seven items
for each media (IM: alpha = 0.89; internet voice: alpha = 0.98; shared whiteboard: alpha
= 0.96). The survey items are provided in the Appendix.

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Table 1. Perceived experiences and media richness of senders and receivers.
Perceived experience
Mean (Standard deviation)
Time
period
Senders
(n = 19)
T0
T1
T2
T3
Receivers
(n = 25)
T0
T1
T2
T3
∗

Perceived media richness
Mean (Standard deviation)

Topic

Partner

IM

IV∗

SWB∗

IM

IV

SWB

5.47(0.74)
5.80(0.61)
5.91(0.61)
5.93(0.73)

n/a
3.01(1.26)
3.29(1.42)
3.56(1.51)

5.34(1.58)
5.42(1.07)
5.56(1.08)
5.82(1.02)

2.80(2.13)
4.45(1.32)
4.55(1.45)
4.82(1.53)

2.23(1.79)
3.81(1.04)
4.74(1.29)
4.83(1.43)

4.77(1.24)
4.76(0.99)
4.85(1.05)
4.94(1.10)

3.11(2.37)
4.71(1.52)
4.95(1.39)
4.86(1.39)

2.46(1.82)
4.17(1.31)
4.53(1.15)
4.67(1.10)

3.47(1.30)
3.92(1.35)
4.15(1.32)
4.68(1.24)

n/a
3.29(1.33)
3.51(1.46)
3.78(1.40)

5.17(1.43)
5.54(1.10)
5.73(1.06)
5.70(1.18)

1.63(1.22)
3.79(1.60)
3.94(1.81)
4.58(1.75)

1.12(0.60)
4.46(1.00)
4.66(1.01)
4.99(0.93)

4.11(1.29)
4.54(1.08)
4.50(1.12)
4.87(1.08)

1.76(1.43)
4.34(1.93)
4.54(1.87)
4.91(1.60)

1.23(0.79)
4.19(1.14)
3.97(1.12)
4.46(1.24)

Note. IV = Internet Voice; SWB = Shared Whiteboard.

4. Analysis and Results
4.1. Perceived experiences and media richness
Table 1 summarizes the mean responses regarding perceived experiences and media richness
for both senders and receivers. T0 represents the results of the pre-survey, with T1 to T3
reflecting the surveys completed following each of the three KT sessions.
4.1.1. Perceived experiences: Testing hypotheses H1a and H1b
To address our first hypothesis (H1a) regarding whether both senders and receivers acquire
experiences (topic, partner, and media) over time, we ran a series of repeated-measures
multivariate analysis of variance (MANOVA) tests contrasting the first and last time periods.
Since we performed two contrasts for each experience measure, we used a Bonferroni
adjustment to control familywise error as suggested by Keppel and Wickens (2004). This
adjustment lowers the critical alpha to 0.025 for significance. We also calculated the partial
omega squared, ω̂2 , effect sizes to provide estimates of the treatment effect. The partial
omega squared expresses the variability of the effect relative to the error used to test it (the
partial measure.) The partial measure is the most useful in this case because the variability
does not include the variability among subjects, which is most appropriate for the withinsubjects portion of the analysis (Keppel and Wickens 2004).
For senders, over time (T0 to T3), there was a significant increase in perceived partner
(F = 7.52, p < .025, ω̂2 = .21), internet voice (F = 18.71, p < .001, ω̂2 = .41), and
shared whiteboard (F = 21.94, p < .001, ω̂2 = .45) experiences. There was no significant
increase in IM experience or perceived topic experience for senders. The topic experience
result is not surprising given the asymmetric KT context of the experiment.

ROLE-BASED EXPERIENCES, MEDIA PERCEPTIONS

375

For receivers, over time (T0 to T3), there was a significant increased in perceived topic
(F = 10.81, p < .01, ω̂2 = .23), internet voice (F = 37.85, p < .001, ω̂2 = .53), and shared
whiteboard (F = 521.35, p < .0001, ω̂2 = .94) experiences. Not surprisingly, the recipients
significantly gained in their perceptions of topic experience over time. Like senders, there
was no significant increase in IM experience. Conversely, unlike senders, there was no
significant increase in perceived partner experience for receivers.
To examine these experiential gains in more detail, we contrasted the measures taken
before and after each session (T0-T1, T1-T2, and T2-T3). This examination provides insights
into the evolution of acquired experiences. Although the MANOVA results indicate that
senders perceived an increase in partner experience from T0 to T3, there were no significant
differences across individual time periods. Together, these results indicate that the session to
session differences were incremental, but they amounted to a significant difference over time.
With regard to topic experience, receivers exhibited significant gains following the first
(T0-T1: F = 4.82, p < .05) and second (T1-T2: F = 5.71, p < .025) sessions. Thus, the
acquisition of topic experience for receivers largely occurred during the first two sessions
when data modeling concepts were being transferred.
Both senders and receivers exhibited a significant gain in experience with internet voice
(senders: F = 17.37, p < .001; receivers: F = 29.06, p < .0001) following the first session
(T0-T1), but not following any other time period. Thus, the acquisition of internet voice
experience largely occurred during the first session.
The shared whiteboard experiences showed different patterns for senders and receivers.
Senders reported a significant gain in shared whiteboard experience following the first
(T0-T1: F = 10.93, p < .01) and second (T1-T2: F = 22.62, p < .001) sessions, but not
following the third (T2-T3) session. During the first two sessions, senders were increasingly
using (and acquiring experience with) the shared whiteboard as they illustrated and transferred data modeling knowledge. Conversely, receivers exhibited a significant increase in
shared whiteboard experience following the first session (T0-T1: F = 274.74, p < .0001),
but no significant acquisition following session 2 (T1-T2). Following the third session,
during which they used the shared whiteboard to present their data modeling solutions,
receivers exhibited a significant increase in experience (T2-T3: F = 6.16, p < .025).
Overall, the above analyses provide partial support for H1a. That is, consistent with CET,
both senders and receivers do gain experiences over time, albeit in different ways.
To address our second hypothesis (H1b) regarding whether senders and receivers vary in
their perceptions of acquired experiences, we ran a series of repeated-measures MANOVAs
examining the results for each group which would indicate whether one group had significantly higher perceptions of experiences than the other. Additionally, we conducted t-tests
for each time period to determine more precisely when the between groups’ experience
perceptions significantly differed during the KT process.
The results of our analysis indicate that between senders and receivers, there was a
significant difference in perceived topic experience across all time periods (F = 55.17,
p < .0001). That is, in all time periods (T0 to T3), receivers acquired significantly greater
topic experience than senders (T0: t = 6.01, p < .0001; T1: t = 5.49, p < .0001; T2: t =
5.24, p < .0001; T3: t = 3.90, p < .001). Again, this is not surprising given the asymmetric
nature of the process wherein the receivers were the targets of the KT.

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There was no significant difference in perceived IM experience between senders and
receivers during any time periods. As reported above, neither senders nor receivers exhibited
any appreciable change in their IM experience over the course of the experiment.
For perceived internet voice experience, there was an overall significant difference (F =
7.10, p < .01) between senders and receivers. But, the t-test result was significant only prior
to the start of the experiment (T0) (t = 2.30, p < .05), with senders reporting higher initial
experience. Even though senders began with a significantly higher internet voice experience
level, that experience gap was closed by the end of the first session (T1) when significant
gains were reported by each group (as reported above). In essence, senders and receivers
converged in their perceptions of this experience.
With regard to perceived shared whiteboard experience, senders began (T0) with a significantly higher level of experience (t = 2.90, p < .01). Following the first session (T1),
however, receivers surpassed the senders leading to significantly higher level of perceived
shared whiteboard experience (t = 2.10, p < .05). No further significant differences were
found following the second (T2) or third (T3) sessions, again suggesting some convergence
in perceived experience.
The above analyses provide partial support for H1b – specifically, at distinct time points
during the KT process, senders and receivers differ in some perceptions of acquired experiences.
4.1.2. Perceived richness: Testing hypotheses H2a and H2b
To address our third hypothesis (H2a) regarding whether both senders and receivers expand
perceptions of media richness over time, we ran a series of repeated-measures MANOVA
tests contrasting the first and last time periods. Again, we used a Bonferroni adjustment to
control familywise error.
For senders, over time (T0 to T3), there was a significant increase in perceived media
richness for internet voice (F = 12.75, p < 0.01, ω̂2 = .31) and shared whiteboard (F =
17.43, p < .001, ω̂2 =.39). There was no significant increase in perceived richness for IM.
For receivers, over time (T0 to T3), there was a significant increase in perceived media
richness for all three media: IM (F = 7.94, p < .01, ω̂2 =.18), internet voice (F = 40.61,
p < .0001, ω̂2 = .54), and shared whiteboard (F = 125.76, p < .0001, ω̂2 =.79).
To examine the expansions in perceived richness in more detail, we again contrasted the
measures taken before and after each session (T0-T1, T1-T2, and T2-T3). This examination
provides insights into the evolution of richness perceptions over time.
While the MANOVA results indicate that receivers perceived an expansion in IM richness
from T0 to T3, there were no significant session to session differences. Again, this suggests
that these session to session differences were incremental in nature, but when examined in
sum (i.e., over time) the differences are significant.
Following the first session, both groups exhibited a significant expansion in the perceived
richness of internet voice (T0-T1 – senders F = 30.14, p < .0001; receivers F = 9.67,
p < .01) and shared whiteboard (T0-T1 – senders: F = 7.87, p < .01; receivers: F = 145.90,
p < .0001). Subsequently, neither senders nor receivers exhibited any further significant
expansions in perceptions of internet voice richness. Senders also exhibited no additional
expansions in perceptions of shared whiteboard richness. Conversely, while receivers did not

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377

significantly change their view of shared whiteboard richness following the second session
(T1-T2), they did exhibit a significant increase in richness following session 3 (T2-T3) (F
= 5.80, p < .025), during which they presented their data modeling solutions, typically via
the shared whiteboard.
Overall, the above analyses provide partial support for H2a. Consistent with CET, both
senders and receivers did perceive expansions in media richness perceptions for some (or
all) of the media, although the timing of perception changes varied by role.
Finally, to address our fourth hypothesis (H2b) regarding whether senders and receivers
vary in their perceptions of media richness, we ran a series of repeated-measures MANOVA
results for each group which would indicate whether one group had significantly higher perceptions of media richness than the other. T-tests were again conducted for each time period
to determine more precisely when the between groups’ richness perceptions significantly
differed during the KT process. The results of our analysis indicate that between senders
and receivers, the only significant differences in perceived richness were with initial (T0)
perceptions of internet voice (t = 2 .35, p < .025) and shared whiteboard (t = 3.03, p < .01),
with senders beginning with higher richness perceptions.
Based on this, H2b is not supported. Rather, our results suggest some level of congruence between senders and receivers regarding the richness of the various media, despite
differences in perceptions of acquired experiences, reported earlier.

4.2. Media richness perceptions and KT success: Testing hypothesis H3
To examine our last hypothesis (H3) regarding whether congruence in media richness
perceptions influences KT success, for each media and by time period (T1, T2, and T3)
we calculated perceived media richness difference scores for each dyad. Specifically, we
calculated the absolute value of the difference between perceptions of media richness by
the sender and receiver; thus, providing three difference scores for each dyad for each of
the three time periods.1 These scores were then used in regression equations to determine
which, if any, were significantly related to KT success, i.e., as reported by the receiver in
terms of a increases in knowledge understanding following each of the three KT sessions
(T1, T2, and T3). In addition to these self-reported measures of KT success, as noted earlier,
one of the course instructors evaluated the quality of the data modeling assignment (on a 10
point scale, where 10 is high) completed by the receivers and handed in following the third
session.2 As such, we also examined whether congruence in media perceptions following
the third session was related to the objective evaluations of KT success.
To examine the relationship between congruence in media richness perceptions and
KT success, we conducted a regression analysis. Following the first session (T1), receivers self-reported knowledge understanding (or KT success) was significantly related
to congruence in perceptions of IM (F = 4.93, p < 0.05, r 2 = .24), but the beta coefficient (.59) was positive. Contrary to our expectations, this suggests that convergence
in IM richness negatively affected advances in knowledge understanding. During this
time period, neither internet voice nor shared whiteboard were significantly related to KT
success.

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Following the second session (T2), the results indicate that congruence in media richness
perceptions of both IM and the shared whiteboard were significantly related (p < .05) to
KT success (IM: F = 4.67, r 2 = .23; shared whiteboard: F = 4.65, r 2 = .23). Congruence
in perceptions of internet voice richness was related to KT success, although at a lower
significance level (F = 3.05; p < .10, r 2 = .16). Both shared whiteboard and internet
voice have negative beta coefficients (respectively −.40 and −.61), thus suggesting that
congruence was positively related to KT success. Conversely, once again, IM had a positive
beta coefficient (.62), suggesting that congruence decreased KT success.
Following the third and last session, receivers self-reported knowledge understanding
was significantly related to congruence in perceptions of shared whiteboard (F = 4.86, p <
.05, r 2 = .23). The beta coefficient is negative (−.60), thus suggesting that congruence was
positively related to KT success as reported by the receiver. Neither IM nor internet voice
were significantly related.
We also tested the relationship between congruence in media perceptions (following the
third session) and the instructor’s objective evaluations. Here, congruence in perceptions of
shared whiteboard was significantly related to the objective measure of KT success (F =
5.85; p < .05, r 2 = .27). Again, the beta coefficient is negative (−.35), indicating a positive
relationship.
The above analyses provide partial support for H3. Evidence suggests that two media –
internet voice and shared whiteboard – were positively related to advances in knowledge
understanding on the part of the receivers during the second session. Similarly, the shared
whiteboard played a key role with regard to KT success during the last session and as related
to instructor’s objective evaluations.

5. Discussion
The transfer of knowledge can be complicated by a variety of factors, particularly when
electronic media is used as the primary means of communication. In an asymmetric KT
context the parties involved have specific role behaviors as senders (sources) of knowledge
and receivers (recipients) of knowledge. Past research suggests that the KT process and its
success (i.e., knowledge understanding) are affected by various experiences such as those
with communication partner(s) and the topic itself (Argote and Ingram 2000). Along with
these experiences, CET (Carlson and Zmud 1999) suggests that experience with electronic
media will serve to shape media richness perceptions. To date, however, there has been
little research that has explored the relationships between role-based (sender and receiver)
behaviors, the acquisition of experiences, and expansions in media richness perceptions.
Furthermore, while past research has largely focused on perceptions (and use) of a single
media (or on the choice between two), we examined these relationships in a multi-media
environment. Such an environment is more reflective of today’s realities in that it is more
likely that individuals will use multiple media (even simultaneously) to affect KT (Massey
and Montoya-Weiss 2006). We proposed that, particularly in the context of asymmetric KT,
the acquisition of experiences and expansions in media richness perceptions may unfold
differently for senders and receivers. Furthermore, when media is the primary vehicle for

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379

communication, we also proposed that congruence in richness perceptions between KT
participants will be positively related to KT success.
Our results contribute to the literature in three important ways. First, we provide evidence
that in an asymmetric KT context, roles do matter relative to the acquisition of experiences
and expansions in media richness perceptions. Second, despite some differences in acquired
experiences, our results suggest that senders and receivers converge in their perceptions of
acquired experiences et al evolve to shared (or congruent) perceptions of media richness.
Third, our results provide evidence that sender-receiver congruence in media richness perceptions influences KT success. Tables 2 summarizes the significant findings, as related to
the testing of the hypotheses (H1a, H1b, H2a, H2b) concerning the role-based perceived
experiences and expansions in media richness, and will be used to facilitate a discussion of
these results.
As Table 2 (see: H1a and H2a) shows, senders and receivers did, in fact, exhibit increases
in some experiences as well as an expansion in some or all media richness perceptions over
time (T0-T3). While these findings are consistent with the expectations of CET (Carlson
and Zmud 1999), they illustrate that roles matter, particularly in an asymmetric KT context.
More specifically, with regard to partner and topic experiences, senders exhibited an
increase in partner experience, while receivers gained topic experience (see H1a). It may
be that because senders were already familiar with the topic, they were more able to learn
about their partner than were receivers who were unfamiliar with the topic. Further, due
to senders’ role as KT source, throughout the exercise they were continually ascertaining
the level of knowledge understanding on the part of the receivers, while the receivers were
more focused on the topic than the partner. Past research has found that interaction in a
computer-mediated environment tends to be task-oriented (Bordia 1997). For receivers, this
may have been heightened due to the asymmetric KT context. Thus, our results provide
evidence that the task orientation may be role-based.
With regard to media experiences, both senders and receivers gained internet voice and
shared whiteboard experience, but no IM experience (see H1a). The initial level of IM
experience (relative to internet voice and shared whiteboard), as well as its stability over
the three sessions, is likely due to the fact that college students constitute a considerable
population of IM users (Pew Research 2005; Flanagin 2005). The session contrasts highlight
that experience gains for internet voice largely occurred during the first session (T0-T1) for
both groups. Once they learned how it worked, no further perceived acquisition of experience
occurred. Conversely, the session contrasts for shared whiteboard experience appears to be
tightly coupled to tasks, which varied by session and sender-receiver KT roles. Specifically,
both groups exhibited gains following the first session (T0-T1) when they were first exposed
to the media. Subsequent gains in the second session (T1-T2) for senders reflected their
intensive KT efforts, while in session three (T2-T3), receivers were extensively using the
media to illustrate and transfer their data modeling solutions. Once again, the results support
a role-based view of the interaction among media and the unfolding KT process.
Our results also suggest that experiences are largely perceived to be acquired in the
earlier stages of the KT process, regardless of role, with the largest gains exhibited following
the first session. Not surprisingly, our results also indicate media experience (here, shared
whiteboard) is predicated on use, as evidenced by session-based differences between senders

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Table 2. Role-based experiences and richness perceptions.
Perceived acquisition of experiences
Results of hypotheses
H1a:
Partial support

H1a:
Over time
(T0 to T3)
Session contrasts

H1b:
Partial support

H1b:
Points in time
(T0, T1, T2, T3)

Senders

Receivers

Partner1
–
IV
SWB
–
IV: T0-T1
SWB: T0-T1, T1-T2
Senders vs. receivers

–
Topic
IV
SWB
Topic: T0-T1, T1-T2
IV: T0-T1
SWB: T0-T1, T2-T3

Topic: T0, T1, T2, T3 – receivers > senders
IV: T0 – senders > receivers
SWB: T0 – senders > receivers
SWB: T1 – receivers > senders
Senders

H2a:
Partial support

H2a:
Over time
(T0 to T3)
Session contrasts

H2b:
Not supported

H2b:
Points in time
(T0, T1, T2, T3)

–
IV
SWB
IV: T0-T1
SWB: T0-T1

Receivers
Perceived expansion in media richness
IM
IV
SWB
IV: T0-T1
SWB: T0-T1, T2-T3

Senders vs. receivers
IV: T0 – senders > receivers
SWB: T0 – receivers > senders

Notes. IM (instant messaging); IV (internet voice); SWB (shared whiteboard).
1
Partner experience over time is measured from T1-T3.

and receivers. Additionally, our between subjects analysis indicates that, as the KT process
unfolds, participants converge in their perceptions of media experiences. Again, due to the
asymmetric KT context, it is not surprising that significant differences in topic experience
were present for all time periods (see H1b).
With regard to media richness perceptions, CET (Carlson and Zmud 1999) suggests
that acquired experiences (partner, topic, media) will lead to expansions in media richness
perceptions. As Table 2 (see H2a) shows, senders exhibited an expansion in richness perceptions of internet voice and shared whiteboard, but not IM. Conversely, receivers expanded
in richness perceptions for all three media. As we consider the link between experiences and
media richness perceptions, our results suggest that at least in a role-oriented asymmetric KT
context, experiences may not be of equal importance. Specifically, while both groups gained
internet voice and shared whiteboard experience, they differed in that senders gained partner experience while receivers gained topic experience. Interestingly, receivers expanded
in their perceptions of IM richness, despite the fact they exhibited no perceived gains in

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Table 3. Congruence in media perceptions and KT success.
Congruence – KT success

H3: Partial support

Time period

IM

IV

SWB

T1
T2
T3

Negative∗
Negative∗
ns

ns
Positive∗
ns

ns
Positive∗ ∗
1
Positive∗

Notes:∗ p < .05, ∗∗ p < .10.
IM (instant messaging); IV (internet voice); SWB (shared whiteboard).
1
SWB was positively related to KT success for both self-reports and objective
evaluation measure.

IM experience. One possible explanation is, as Massey and Montoya-Weiss (2006) suggest, that in a multi-media environment, experience with and/or richness perceptions of one
media may influence perceptions of another media. That is, experiences and perceptions of
internet voice and/or shared whiteboard may have positively influenced perceptions of IM.
The session contrasts provide insight into when expansions in media richness perceptions occurred and how they relate to acquired experiences. This may also help explain
why we found no evidence of differences between senders and receivers in terms of perceptions of media richness following each session (see H2b). As Table 2 (see H2a) shows,
expansion in richness perceptions mirrored the acquisition of experiences (see H1a). Since
partners acquired experiences and perceived expansions in richness early in the KT process,
they quickly converged in their richness perceptions. For example, for both senders and receivers, internet voice experience was largely acquired during the first session (T0-T1), with
expansion in richness perceptions of internet voice also occurring here. The relationship
between shared whiteboard experience and richness perceptions provides some initial evidence that media perceptions expand and contract relative to the task at hand. Importantly,
by examining KT roles and task activities, we were able to examine the relative evolution
of experiences and richness perceptions of this media.
Finally, Table 3 summarizes the significant results as related to the testing of our third
hypothesis (H3) regarding whether sender-receiver congruence in media perceptions influences KT success.
Our results provide evidence that shared media perceptions do influence advancements
in knowledge understanding on the part of the receiver. However, while KT partners may
possess shared meanings about what a media is good for, congruence can have a negative
effect on KT. For example, congruence in perceptions of IM had a significant, yet negative
effect on KT success during the first two sessions (T1 and T2). The first session centered
on “getting to know one another”, becoming familiar with the three media, and preliminary
efforts to transfer basic concepts. Partners may have spent relatively little time discussing
basic concepts; rather using IM for non-KT task related communication activities (e.g.,
socializing, discussing the other media), thus leading to a negative impact on receivers
perceptions of actual KT. Conversely, during the second session, both internet voice and
shared whiteboard were significantly and positively related to KT success. Here, senders
extensively used both media to transfer and illustrate more intermediate concepts. Given

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that senders and receivers shared perceptions about what the capabilities of these two
media were relative to the task, KT was advanced. IM continued to have a negative effect
during this session. While partners shared perceptions of IM, it may be that IM-based
communication was distracting for the KT task. Finally, during the last session, shared
whiteboard had a significant, positive effect on KT. Here, the receiver used this media to
present their assignment solution to the sender, gaining any necessary feedback and further
instruction. Congruence in perceptions of the shared whiteboard, following this session,
was also positively related to the objective evaluations (of the receivers efforts) conducted
by the instructor.
Overall, our results illustrate the interplay between media capabilities and KT activities
– task-technology fit is important. Here, internet voice and shared whiteboard both took
on central roles in advancing knowledge understanding. Importantly, our results also illustrate that congruence in media perceptions between KT partners plays a significant role in
advancing knowledge understanding. But, congruence in perceptions without fit relative to
the task may have a negative effect as evidenced by our findings with respect to IM.
To summarize, our results suggest that while various experiences influence richness
perceptions, when experiences are acquired early, richness perceptions are shaped early.
Further, task needs appear to drive experience acquisition, and thus richness perceptions.
Essentially, necessity is the mother of richness. Our findings also provide preliminary evidence that once participants ascertain the utility of a particular media, richness perceptions
may reach a maximum (Massey and Montoya-Weiss 2006). Consistent with past research
(Walther 1992; Markus and Keil 1994; Burke and Chidambaram 1999), our between subjects
analysis suggests that, as the KT process unfolded, participants did converge in perceptions
of media richness. This is an important finding for KT, particularly in light of past research that has emphasized the importance of congruence between member-task (roles) and
member-tool (media) components (Nadler and Tushman 1980; Argote 1982). Our results
demonstrate that congruence in media perceptions is related to KT success.
It is also important to note that while asymmetric KT has been widely observed in
practice (e.g., technology transfer, new product development), due to global competition and
economic pressures we are increasingly witnessing organizations extending their boundaries
from traditional co-located settings to virtual settings with electronic media playing a central
role in interaction. Today, one can easily imagine senders of knowledge in one location and
receivers in another, each attempting to advance knowledge understanding using a myriad
of media. Our results provide deeper insights regarding the relationship between rolebased behaviors and unfolding perceptions, and provide evidence that congruence in media
perceptions influences the success of KT in an asymmetric context.

6. Limitations and Directions
Certain limitations of this research must be acknowledged. First, we focused our exploratory
study on an asymmetric KT context involving a dyadic relationship between a sender and
receiver. This was important in order to examine specific differences in role-based KT. However, the extent to which our findings generalize to other KT structures and multi-partner

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383

relationships that may result in different KT patterns warrants further research. Second,
the use of student subjects may limit the generalizability of our results. However, given
students’ general familiarity and comfort with technology, issues associated with computer
anxiety are largely eliminated. Thus, student subjects provide a useful sample for this investigation. It is important to note, however, that additional research should be conducted
with an older, less computer literate subject pool in order to examine impacts of computer
anxiety, computer literacy, and age (to name a few). Third, due to the controlled nature of our
exploratory experiment, we allowed the participants to have only three synchronous meetings. Additionally, our participants had limited initial experience with two of the media and
no history of working together. As such, our study does not account for the impacts of extended partner or media familiarity on experience and richness perceptions. Future research
involving longer duration KT, participants using both synchronous and asynchronous media, and participants with some working history as well as some level of media experience
is warranted. Fourth, except for post-experimental objective evaluation of KT success, our
study relied on self-report measures of perceptions. While this is a common technique in
behavioral research, content-coding of the interactive sessions may provide deeper insights
into media use relative to KT activities as well as the nature and timing of the relationships
uncovered in this study. For example, we may gain deeper insight into why IM use, despite
congruence in perceptions, was negatively related to KT success. Finally, in order to minimize non-mediated interaction between sender and receiver, we relied on geographically
distributed subjects. While geographic location may confound with role, it is important to
note that in six pairs, senders and receivers were co-located (unbeknownst to the partners).
Thus, while we can not entirely rule out confounds associated with location, school, or program, evidence suggests that these dyads performed similarly to the other dyads. However,
future studies incorporating a more diverse group of subjects would be extremely valuable
in helping to identify relevant factors that influence role-related behaviors. In sum, further
empirical testing involving both controlled experiments and field studies will advance efforts to fully explore the relationship between KT and perceptions of experiences and media
richness.

7. Conclusion
Although the benefits of KT have been documented in many settings, much research remains to understand the factors that support or impede transfer. Because people play a
critical role in the success of KT, research on the role of KT participants (social relationships) as well as alternative KT structures (member-topic relationships) is central to
advancing understanding. At the same time, transferring knowledge among human entities that largely communicate via electronic media presents new challenges and avenues
for research. KT participants’ perceptions of the utility or richness of alternative media
will influence selection and use and ultimately the effectiveness of KT. In this paper, we
examined the relationship between the role-based experiences and media perceptions in
a controlled, experimental setting. Our findings provide evidence of role-related effects,
convergence in experiences and media perceptions, and a relationship between congruence

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in media perceptions and KT success. We hope that the ideas offered in this paper provide
a basis for future research regarding these complex relationships.
Appendix: Survey Instruments
Experience with Topic – items adapted from Carlson and Zmud (1999).
1. I feel that I am experienced with data modeling.
2. I feel that I am well-versed in the concepts associated with data modeling.
3. I do not feel knowledgeable about data modeling.
Media Experience – items adapted from Carlson and Zmud (1999).
1. I am very experienced using the (instant messaging, internet voice, shared whiteboard)
feature.
2. I feel that the (instant messaging, internet voice, shared whiteboard) feature is easy to
use.
3. I feel competent using the (instant messaging, internet voice, shared whiteboard) feature.
4. I understand how to use all of the options of the (instant messaging, internet voice, shared
whiteboard) feature.
5. I feel comfortable using the (instant messaging, internet voice, shared whiteboard) feature.
6. I feel that I am a novice using the (instant messaging, internet voice, shared whiteboard)
feature.
Experience with Partner – items adapted from Carlson and Zmud (1999).
1.
2.
3.
4.
5.
6.

Overall, I feel that I know my project partner well.
I feel comfortable communicating emotional issues with my project partner.
I feel comfortable discussing personal or private issues with my project partner.
I feel close to my project partner.
I feel that I am not familiar with my project partner.
I feel involved with my project partner.

Media Richness – items 1–4 adapted from Carlson and Zmud (1999), items 5–7 adapted
from Dennis and Kinney (1998).
1. The (instant messaging, internet voice, shared whiteboard) feature allows us to give and
receive timely feedback.
2. The (instant messaging, internet voice, shared whiteboard) feature allows us to tailor our
messages to our own personal requirements.
3. The (instant messaging, internet voice, shared whiteboard) feature allows us to communicate a variety of different cues (such as emotional tone, attitude, or formality) in our
messages.

ROLE-BASED EXPERIENCES, MEDIA PERCEPTIONS

385

4. The (instant messaging, internet voice, shared whiteboard) feature allows us use rich
and varied language in our messages.
5. I could easily explain things using the (instant messaging, internet voice, shared whiteboard) feature.
6. The (instant messaging, internet voice, shared whiteboard) feature helped us communicate quickly.
7. The (instant messaging, internet voice, shared whiteboard) feature helped us to better
understand each other.

Notes
1. There are 18 dyads in this analysis as we could only use dyads for which both sender and receiver completed
all four surveys.
2. Receiver’s self-reported measures of knowledge understanding at the end of the experiment were significantly
related to the instructor’s objective evaluations (F = 11.31, p < .01), suggesting that the self-report measures
provide relatively accurate assessments of changes in knowledge understanding or KT success.

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