Essential knowledge for academic performance: Educating in the

Transcription

Teaching and Teacher Education 37 (2014) 217e234
Contents lists available at ScienceDirect
Teaching and Teacher Education
journal homepage: www.elsevier.com/locate/tate
Essential knowledge for academic performance: Educating in the
virtual world to promote active learning
Gwen Noteborn a, *, Amber Dailey-Hebert b, Katerina Bohle Carbonell a, Wim Gijselaers a
a
b
Maastricht University, The Netherlands
Park University, USA
h i g h l i g h t s
Academia focuses on content knowledge neglecting procedural knowledge.
The labor market demands the development of both.
Simulations offer a way of measuring, training and disentangling both.
Results show procedural knowledge influences academic performance.
Teachers should focus on both types of knowledge benefiting universities and students
a r t i c l e i n f o
a b s t r a c t
Article history:
Received 4 October 2012
Received in revised form
9 August 2013
Accepted 14 October 2013
Education has traditionally focused on the importance of content, and has guided curriculum design
according to this principle. While content knowledge is important, to excel in the labor market today
graduates need to develop procedural knowledge, with greater emphasis on capacity development for
transferable skills. This need is amplified by emergent technologies, which increase the demand to
develop knowledge in this domain. To disentangle and measure the impact of content and procedural
knowledge on academic achievement, the study occurred in a virtual setting. Based on the findings, we
provide recommendations for course designers and course developers to improve students‟
performance.
Ó 2013 Elsevier Ltd. All rights reserved.
Keywords:
Virtual worlds
Procedural knowledge
Content knowledge
Teaching
Educational development
Educational design
Second life
Picture 1
“For the things we have to learn before we can do them, we
learn by doing them.” e Aristotle
1. Introduction
Globalization and competition increase substantially due to the
availability of new technologies, changing the way students elect a
program, university, or course. While it is important to acquire
conceptual knowledge and expertise in a domain (Alexander,
Schallert, & Hare, 1991), to excel in today’s labor market,
* Corresponding author. Maastricht University, Department of Educational
Research and Development, Tongersestraat 53, 6211 LM Maastricht, P.O. BOX 616,
6200 MD Maastricht, The Netherlands. Tel.: þ31 43 38 83895; fax: þ31 43 38 84801.
E-mail address: gcm.noteborn@maastrichtuniversity.nl (G. Noteborn).
0742-051X/$ e see front matter Ó 2013 Elsevier Ltd. All rights reserved.
http://dx.doi.org/10.1016/j.tate.2013.10.008
graduates need to develop procedural knowledge, with a focus on
skills that are transferable across multiple domains and contexts
(Beaudry, Green, & Sand, 2013; Friedman, 2005; Pink, 2006).
Consequently, such increases also change the way students prefer
to learn and the ways in which teachers can provide more flexible
and adaptive education (Christensen & Eyring, 2011). Moreover,
today’s labor market, accelerated by the current credit crunch,
imposes higher demands on workers’ qualification levels (IBM,
2010). Trends in the labor market indicate a shift in demand from
cognitive tasks to practical execution and transferable skills
(Beaudry et al., 2013). Escalating tuition fees and a tight labor
market bring about financial and time constraints, making the
acquisition of procedural knowledge during curriculum, in the form
of internships or part-time jobs, difficult, if not impossible. Such
developments question the nature of current education programs
and demand continuous assessment of how higher education
contributes to the changing demands of the workplace. As a direct
result, today’s graduates must develop procedural knowledge
218
G. Noteborn et al. / Teaching and Teacher Education 37 (2014) 217e234
Picture 1.
(know-how) as well as conceptual knowledge (know what) in their
domain (Claxton, Lucas, & Webster, 2010; Lucas & Claxton, 2009;
Schank, 2011) in order to increase their job prospects (European
Centre for the Development of Vocational Training, 2010). Therefore, universities can facilitate and foster such competency development, and support educators to explore areas, which promote
student learning and development.
1.1. A different kind of skillset
While employers seeks individuals who can demonstrate an
execution of their knowledge to thrive in the complexity of industry (IBM, 2010; Johnson et al., 2013), higher education has
been criticized for failing to develop such characteristics and
struggles to prepare young people for challenging new jobs in
times of exponential change (Boyatzis, Stubbs, & Taylor, 2002;
Frenk et al., 2010; Kanes, 2011). Universities are said to focus on
teaching conceptual knowledge at the expense of procedural
knowledge (Belei, Noteborn, & de Ruyter, 2011; Gijselaers &
Milter, 2009; Gijselaers & Milter, 2010; Scardamalia & Bereiter,
2006) , potentially affecting the ability of graduates to perform
well in their future jobs (Laveñe, 2006; Page & Mukherjee, 2007).
Some authorities suggest that current changes in the labor
market require a fundamental shift in the design and purpose of
education in general - higher education in particular (Barber,
Donnelly, & Rizvi, 2013; Harasim, 2012), thereby highlighting the
need for educators to refocus their teaching (Oblinger & Oblinger,
2005), from theoretical knowledge to transferable skills (Claxton
et al., 2010; Scardamalia & Bereiter, 2003).
Research in higher education consistently demonstrates that
procedural knowledge is best taught through active learning approaches (Candy, 2000; Wooldridge, 2006). Still, with the exception
of early adopters and innovators in the field, higher education remains rather static, with limited opportunities to integrate practice
in meaningful ways (Belei et al., 2011; Graeff, 2010; Scardamalia &
Bereiter, 2006; Noteborn, Bohle Carbonell, Dailey-Hebert, &
Gijselaers, 2012). Therefore, despite the prevalence of student
projects and practical assignments, a gap between theory and
practice still exists. Yet, one advantage of the increased prevalence
and use of emergent technologies is the ability to create unique
learning experiences and to connect learners in new ways.
1.2. A fundamental shift
Computer simulations have been lauded for their ability to
address difficult, or even impossible, to observe phenomena (Çepni,
Taş, & Köse, 2006; Urban-Woldron, 2009). Recently, educators have
started to adopt advanced simulations, such as virtual worlds, to
support learning in education and to help learners develop essential knowledge (Pena & Antonio, 2010).
There is a growing consensus that virtual learning spaces offer
an optimal context to promote the merger of content and execution
(Anderson, 1995; Fink & Fink, 2009; Yi & Davis, 2003), suggesting
such environments can enable learners to develop the capacity for
applying procedural knowledge in parallel to their conceptual
knowledge acquisition. As the online learning movement becomes
more prevalent, a new capacity for procedural knowledge in
emergent technologies also grows across all domains (Clift, Mullen,
Levin, & Larson, 2001; Niess, 2005; Oblinger & Oblinger, 2005).
Institutions scramble to re-create the face-to-face experience online and often return to traditional course design, which simply
moves existing content online (Lohr, 2009; Niess, 2005; Wang,
2009). Furthermore, there is an expectation that our educators
develop a depth and breadth in conceptual knowledge, yet minimal
attention is given to the transferability of this knowledge in relation
to context (Niess, 2005); resulting in a lack of the necessary support
for such efforts. As mentioned above, the need for more research on
how to integrate emerging technologies in education is apparent.
Yet, innovative educators who wish to integrate technology in a
meaningful and intentional way often find teacher preparation and
support to be lacking (Allen & Seaman, 2007; Blin & Munro, 2008;
Niess, 2005). As we live in an adaptive and dynamic world, we need
to acknowledge the adaptive and dynamic nature of learning and
development, and consider a paradigm shift in how we think about
learning and training (Salas & Rosen, 2010).
In summary, simulations may offer an effective and efficient
context for the development of procedural knowledge in higher
education, particularly in domains with difficult to observe phenomena, preparing students for their future jobs and changing labor market needs. Yet, there is little research examining the effect
of simulations and, in particular, how simulations contribute to the
development of learning.
The current study examines the role of procedural and conceptual knowledge in the context of the virtual world (Second Life),
by disentangling both concepts and analyzing their impact on academic performance. Additionally, this paper will discuss the
resulting implications for educators who wish to use the context of
virtual environments to support the development of procedural
and conceptual knowledge.
2. Conceptual framework
2.1. Procedural & conceptual knowledge
Studies on learning and instruction demonstrate the pivotal role
of knowledge, and the process of knowing, which lead to a greater
understanding of the evolution and development of education
(Rittle-Johnson, Siegler, & Alibali, 2001). Knowledge is attributed a
wide variety of properties and qualities (De Jong & FergusonHessler, 1996). These various and wide-spread properties and
qualities of knowledge result in many fine-tuned terms for
describing the knowledge state of individuals (De Jong & FergusonHessler, 1996).
2.1.1. Definition of terms
Theories on learning and development distinguish between
conceptual and procedural knowledge (e.g., Anderson, 1993; Bisanz
& LeFevre, 1992; Greeno, Riley, & Gelman, 1984; Karmiloff-Smith,
1994; Piaget, 2013). These two types of knowledge exist on a continuum and cannot always be separated, however, the two ends of
the continuum represent distinct types of knowledge (RittleJohnson et al., 2001). Despite the agreement on both types of
knowledge, various notions exist for the definitions of procedural
and conceptual knowledge (Baroody, Feil, & Johnson, 2007; Star,
2005).
De Jong and Ferguson-Hessler (1996) make a case and point to
the careful use of these terms, as popular use confounds knowledge
categories without knowledge properties. Within this manuscript,
conceptual and procedural knowledge are defined as follows:
Conceptual knowledge is static knowledge about facts, concepts, and
principles (Rittle-Johnson et al., 2001) that apply within a certain
domain (Byrnes & Wasik, 1991; Greeno, 1978; Van Berkum & de
Jong, 1991). In the context of marketing/branding, conceptual
219
knowledge entails the knowledge of marketing, branding and
advertising concepts, facts and principles (e.g. the theoretical
distinction between points of parity and points of difference).
Procedural knowledge is defined as follows: Procedural knowledge
contains actions or manipulations that are valid within a domain
(De Jong & Ferguson-Hessler, 1996) and has the ability to execute
action sequences to solve problems (Baroody, 2003; LeFevre et al.,
2006; Rittle-Johnson et al., 2001). In the context of marketing/
branding, procedural knowledge entails skills such as; product
design, development and implementation of advertising strategies
and actual product selling.
2.1.2. Interdependence and order of appearance
Competing theories have been proposed regarding the developmental relations between conceptual and procedural knowledge (Rittle-Johnson et al., 2001). Distinguishing between
procedural knowledge and conceptual knowledge can be difficult
(Bisanz & LeFevre, 1992; Rittle-Johnson & Siegler, 1998), as reflected by the discord on the order of appearance of conceptual
and procedural knowledge. In general, there are three views on
both the development of procedural and conceptual knowledge
and their interrelation (Schneider & Stern, 2005). Rittle-Johnson
et al. (2001) distinguish between concept-first and procedurefirst theories. According to concept-first theories, conceptual
knowledge is present in the learners mind before their procedural
skills are developed (Gallistel & Gelman, 1978; Gelman & Meck,
1983), whereas procedure-first theories suggest the opposite
(Briars & Siegler, 1984; Frye, Braisby, Lowe, Maroudas, & Nicholls,
1989). Based on the fact that there is empirical evidence for
both theories, another alternative known as the theory of iteration
(Iterative Model), suggests the possibility of bidirectional causal
links between conceptual and procedural knowledge (RittleJohnson et al., 2001). However, recent studies in the field of
neuroscience have proven that procedural knowledge and conceptual knowledge do not need to be interrelated, but can also be
separated in the mind (Atallah, Lopez-Paniagua, Rudy, & O’Reilly,
2007); that is, learning a new skill and expressing it are two
different steps that can be dissociated (Lerchner, La Camera, &
Richmond, 2007).
2.1.3. Emphasis and importance
There is a perception that procedural knowledge acquisition has
been de-emphasized and regarded as less important than conceptual knowledge, with dismal consequences for student learning
(e.g., Budd et al., 2005). Some researchers are quite explicit in their
belief that procedural knowledge should play a secondary, supporting role to conceptual knowledge in student learning (e.g.,
Pesek & Kirshner, 2000). Even though scholars recognize the
importance of procedural knowledge (Roberts, Gott, & Glaesser,
2010; Schiller, Goodrich, & Gupta, 2013; Star, 2007), the lack of
empirical research on procedural knowledge infers that few researchers are comfortable with inquiry that foregrounds procedural
knowledge (Star, 2007).
To date, it remains unclear how conceptual and procedural
knowledge can be measured independently of each other (Roberts
et al., 2010; Schneider & Stern, 2005). However, analyzing the
importance of either construct, or their impact on student learning
in the form of academic performance, demands a disentanglement
of both concepts.
2.2. Active learning
Active learning utilizes three dimensional multiuser virtual
environments that allow novel forms of learning and collaboration
(Kozinets & Kedzior, 2009; Salmon, 2009). In the past decade active
220
learning and experiential learning have been widely adopted in
multiple domains of study (Ayers & Underwood, 2007; Levin &
Davis, 2007; Wheeler, 2008). Active learning refers to any
instructional method that engages students in the learning process
(Prince, 2004). Research into the effectiveness of active learning
suggests that student learning is best facilitated by engaging students in the tasks through simulating real-life decisions (Laveñe,
2006; Maher & Hughner, 2005; Page & Mukherjee, 2007).
Embedding active learning exercises, which allow students to
perform actions in their domain of study and which enable interaction and reflection, can lead to significant improvements in
learning (Scardamalia & Bereiter, 2003; Yamarik, 2007). Furthermore, learning by doing fosters involvement, engagement and
enjoyment (Jensen & Owen, 2001; Noteborn et al., 2012; Myers,
2010; Wooldridge, 2006).
Computer simulations have been lauded for their ability to
address difficult or impossible to observe concepts (Çepni et al.,
2006; Renken & Nunez, 2013; Urban-Woldron, 2009). This seems
especially applicable to the specific field of marketing and branding
(Gijselaers & Milter, 2009; Graeff, 2010; Noteborn et al., 2012),
which demand a balanced approach between the study of theoretical concepts and the opportunity to experience real-life
branding consequences (Elam & Spotts, 2004). The phenomena of
successfully branding a product might seem apparent, yet it embodies complex underlying principles.
Active learning requires a different teaching approach as well
(Bluestone, 2000, 2007; Graeff, 2010), shifting the role of the
instructor from teacher to mentor or expert (De Freitas & Neumann,
2009). A hallmark of teaching excellence is the ability to give students a learning experience beyond what they can learn from textbooks (Graeff, 2010). Teachers are often uncertain of how to embed
active learning opportunities within their curriculum (De Freitas &
Oliver, 2006), or may perceive the integration of real life elements
as being limited to small classes. While some situations fail to allow
for elaborate practice which resembles real life, new media technologies allow for sophisticated simulations of problem solving context
(Bell & Trundle, 2008; Rutten, van Joolingen, & van der Veen, 2012).
Through such simulations, pupils can add meaning to the theoretical
concepts and reinforce their procedural and conceptual knowledge.
2.3. Virtual worlds as an accelerator
The addition of real-life elements in a course can create constraints (e.g. monetary, time, geographical), however, recent advances in technology enable a simulated experience that allows
students to practice conceptual and procedural knowledge in
context (Galvão, Martins, & Gomes, 2000; Nelson & Erlandson,
2012). Given the vast scope of educational technologies available,
it is important to delineate between (simulation) games and virtual
worlds.
Games are defined as an interactive, goal-oriented activity, with
active agents to play against, in which players can interfere with
each other (Crawford, 2011). Games have a beginning and an end.
Simulation games represent an environment accurately (although
sometimes simplified), and they represent the interactions between players and the environment realistically. Virtual worlds
differ from (simulation) games in the sense that they are persistent
e meaning that the world continues even after users exit the world,
preserving user-made changes. Bell (2008) defines virtual worlds
as “synchronous, persistent networks of people, represented as
avatars, facilitated by networked computers” (p.2).
2.3.1. Characteristics of virtual worlds
Simulations, by means of virtual worlds, serve as an excellent
medium to offer a real life experience (Kozlowski & Bell, 2007;
Schiller et al., 2013), and to increase student performance in a time
efficient manner (Parush, Hamm, & Shtub, 2002). These environments provide an abstract form of reality, as learners are not physically present in this world, but use technology to interact with
people and objects in virtual worlds. Recent reviews identify the
potential of learning in virtual worlds to stimulate student engagement (Jensen & Owen, 2001; Noteborn et al., 2012; Wooldridge,
2006) and perceived usefulness of academic assignments (Lohr,
2009; Nelson, Ketelhut, Clarke, Bowman, & Dede, 2005; Neulight,
Kafai, Kao, Foley, & Galas, 2006). Next, simulations foster the active
discoverer within students and accelerate the learning process
(Drea, Tripp, & Stuenkel, 2005; Haytko, 2006; Schee, 2007) due to
vicarious learning, which also facilitates built-in feedback, cognitive
organization and knowledge retention (Anderson, 1995; Bolt,
Killough, & Koh, 2001; Yi & Davis, 2003). Consequently such
learning can establish connections to previously learned concepts
(Murthy, Challagalla, Vincent, & Shervani, 2008), and contribute to a
deeper understanding across various domains (De Freitas, 2006;
Gijselaers & Schmidt, 1995; Green & Bavelier, 2003). These characteristics provide virtual worlds with learning opportunities that can
only be done online, not in a real classroom (Burbules & Callister,
2000). In contrast to serious games, where simulation stops once
the student logs out and leaves the environment exactly as it was left
upon return, virtual worlds are persistent (Cannon-Bowers, Bowers,
& Sanchez, 2008). This persistence implies that actions continue and
the world evolves irrelevant of the presence of specific players who
can enter the world at any desired time. By means of this persistence,
virtual worlds mimic reality to a greater extent and allow for complex interactions among players and with the environment. Even in
this simplified environment, the simulation is not limited to the
physical aspect of the system, (e.g., selling a product) but can also
incorporate the underlying structure of the task or problem (e.g., the
aspect of competition or social interaction). As a consequence of
such increasing reality, virtual worlds are well suited for education.
Next to the persistent character, virtual worlds facilitate for multiplayer games (Cannon-Bowers et al., 2008). Several people who
are geographically dispersed can interact simultaneously with each
other and/or the virtual world.
2.3.2. Second life by linden lab
Second Life, founded by Linden Lab in 2003, is an example of
such an online virtual world. Second Life is the premier virtual
world (Messinger et al., 2009) and, by far, the most influential one
in corporate learning and higher education (Donnelly, 2010; Hornik
& Thornburg, 2010; Schiller et al., 2013; Warburton, 2009; Ward,
2010). It is a system that provides realistic environments, with a
working representation of reality, where players log in via a webbased application in a world that mimics reality. Within Second
Life, players interact through avatars, a virtual representation of
oneself. The value of Second Life lies in its capability to provide an
authentic replication of reality (Kozlowski & Bell, 2007; Sauvé,
Renaud, Kaufman, & Marquis, 2007). In the case of Second Life,
the setting and thereby the degree of reality, are simplified (Galvão
et al., 2000). Although simplified, the simulation is not limited to
the physical aspect of the system (e.g., riding a bicycle or flying an
airplane), and can also incorporate the underlying structure of the
task or problem (e.g., the aspect of competition or social interaction). Educators (can) limit the various elements in Second Life to
prevent overexposure for students.
2.3.3. Impact on learning
Communication takes place synchronously and instantaneously, via instant messaging or voice chat; a concept being
referred to as immediacy (Wood, 2010). Immediacy offers the
chance for learners to gain direct feedback or assistance from
fellow learners or educators. A special feature of Second Life, in
comparison to other virtual worlds, is that it permits multi-user
online role-playing. Furthermore, users can collaboratively create
and use in-world artifacts such as text, pictures, and threedimensional objects, increasing a sense of community among
players (Wood, 2010). Research shows the importance of immersion, defined as the subjective impression of participation in a
comprehensive, realistic experience (Dede, 2009), which enables
players to gain an understanding of their future work environment
and which allows players to experience an interaction between
elements of their future professional environment (Belei et al.,
2011; Kozlowski & Bell, 2007). Immersion by means of video
games can yield up to 40% improvement in learning over static
didactical approaches such as lecturing (Mayo, 2009). Hence, educators should evaluate these emerging technologies, and the
ways in which they can be effectively used to support teaching and
learning (Tuten, 2009).
221
Literature in education has stressed the need for more studies
which explore the ways virtual technologies can be leveraged for
enhanced learning (Brooks, Burson, & Rudd, 2006; Christian, 2008;
Heinecke, Milman, Washington, & Blasi, 2002; Means & Haertel,
2004; Thackray, Good, & Howland, 2010; Wood, Allen, & Sullivan,
2008). Furthermore, research has indicated several important
outcomes of learning in virtual worlds, such as immersion (Dede,
2009), engagement, enjoyment (Noteborn et al., 2012) and
increased student performance (Cannon-Bowers et al., 2008,
Kozlowski & Bell 2007, Mayo, 2009). Nonetheless, the effectiveness of using Second Life in marketing education has not been fully
assessed despite the few recent studies (Drake-Bridges, Strelzoff, &
Sulbaran, 2011; Tuten, 2009; Wood et al., 2008). In particular, the
underlying cognitive processes and knowledge building, which
take place when learning in virtual worlds, are not addressed
(Renken & Nunez, 2013) and their influence on academic performance remains unclear.
Picture 2. Students interacting within Second Life.
222
2.4. The influence of knowledge on academic performance
A majority of studies on contextualized learning generalize the
effect of technology as a catalyst toward learning (Honebein, Duffy,
& Fishman, 1993; Noteborn et al., 2012; Petraglia, 1998), and refer to
authenticity and emotion as possible explanations for such outcomes. Technology has been used as a context for executing in the
present study, as the virtual world (Second Life), serves as a
learning environment in which students acquire knowledge. Unlike
traditional education, the learning process can be visible in context
to measure conceptual knowledge and procedural knowledge.
However, to fully prepare learners for the workplace, educators
must also understand the effects of both competencies (conceptual
knowledge and procedural knowledge) on academic performance.
The term academic performance is the outcome of education, the
extent to which a student has achieved educational goals (Ward,
Stoker, & Murray-Ward, 1996). Commonly, academic performance
is measured by examinations or continuous assessment; however,
there is no general consensus on how academic performance
should be measured (Imeokparia & Kennedy, 2013). In this study,
academic performance is measured by a combination of course
assessments. Fig. 1 summarizes the relationships analyzed, which
connects the concepts of procedural and conceptual knowledge to
academic performance. As a result of this information and the
conceptual framework previously shared, the following research
question is explored:
Research Question: To what extent do conceptual knowledge
and procedural knowledge relate to student academic performance
in simulated learning environments?
3. Method
3.1. Participants
The sample included 155 students enrolled in an 8-week brand
management course within an International Business program at a
large European university. The university’s pedagogical approach
entailed problem-based learning (PBL), a student-centered pedagogy in which students learn about a subject through the experience of problem solving (Sevilla, 2012).
3.2. Materials
We created an online survey to measure student perceptions of
knowledge and performance through self-evaluation of their skills
and competencies. Additionally, given the intense group work and
team interactions for the learning process, a peer evaluation of
Fig. 1. Conceptual model on the relation between procedural knowledge, conceptual
knowledge and academic performance.
team members’ skills and competencies was also utilized. Peerevaluation was an assessment method used throughout all undergraduate studies and thus students were adequately trained to
evaluate their peers (Van Zundert, Sluijsmans, & van Merriënboer,
2010). Survey questions targeted personal demographics (age, nationality, gender); academic history (major, years of study); technical aspects of the course (technical support, resemblance with
real life, advantages/disadvantages of using Second Life within the
course setting); and a SWOT analysis that consisted of 14 openended questions where students could elaborate on several aspects of the Second Life project. Additionally, the survey measured
two aspects of the learning experience in the course: conceptual
knowledge and procedural knowledge. Academic performance was
measured by a composition of course assessments. Consent for
participation was requested on the first page of the online survey
and the survey was administered online during the last week of the
course. Students were informed on confidentiality practices and
told that participation would not have any impact on their final
grade.
3.3. Measurements
3.3.1. Conceptual knowledge
Conceptual knowledge refers to static knowledge about facts,
concepts and principles that apply within a certain domain. To
examine a student’s conceptual knowledge, experts in the field and
those responsible for the course were consulted. The collaboration
identified several concepts, those considered necessary to excel in
the course and necessary to achieve academic performance, in the
field of brand management. The agreed upon concepts included:
general marketing expertise, brand management expertise, advertising expertise, and expertise in conceptual product ideas. Halfway
through the course, all participants completed the survey to rate
their team members by means of indicating an expert (1 for ‘yes’
and 0 for ‘no’). To account for team size differences, the total score
of each team member was expressed as a percentage of the
maximum score that a team member could obtain.
3.3.2. Procedural knowledge
Procedural knowledge refers to actions that are valid within a
domain and the ability to execute action sequences to solve
problems. To assess procedural knowledge, the collaborative
team of conceptual experts and course coordinators identified 6
actions necessary to achieve success in the course’s virtual
learning environment. The constructs included: 1) designing the
product in Second Life, 2) building a shop in Second Life, 3)
developing advertisement strategy in Second Life, 4) implementing advertisement strategy in Second Life, 5) implementing
advertisement strategy in Real life, and 6) selling the product in
Second Life. The survey offered participants two responses for
each construct to assess their teammates procedural knowledge.
Respondents could select, yes (1) if their teammate possessed this
knowledge or no (0) if the team member did not possess this
knowledge. As with conceptual knowledge, the team member’s
total score was expressed as a percentage of the maximum score
that a team member could obtain to account for team size
differences.
3.3.3. Academic performance
Academic performance is defined as the outcome of education;
the extent to which a student has achieved educational goals (Ward
et al., 1996). In this study, academic performance was measured by
a combination of assessments, measured in an ecologically valid
manner by the student’s final grade in the Brand Management
course. The final grade was composed of the student’s exam grade
(40 %), Second Life team grade (30%) and individual participation
during small group discussions (30%) (Fig. 2).
The exam included five theoretical questions related to the
topic of Brand Management. The exam was essay style, meaning
students had to answer theoretical questions placed in the context
of a case or newspaper article. The total time allowed for the exam
was 3 hours. The exam was closed book. A total of 100 points were
available for the exam and the final exam grade accounted for 40%
of the students’ course grade. The Second Life team grade was
based on group performance indicators which included; 1) total
sales revenue, 2) peer feedback, 3) argumentation for chosen
branding strategies, and 4) creativity and innovativeness. Sales
revenue was measured by multiplying the amount of items sold by
the price per item. Sales revenue was measured on a team level.
Data was collected by analyzing the self-reported sales numbers of
student teams, and by the self-reported purchases of student
customers, in comparison to the raw data files exported from the
Second Life software (Second Life income statistics). Peer feedback
was measured through an extensive obligatory after sales questionnaire, where all buyers had to motivate their reasons for
purchase on a brand management level (conceptual level). Questions in the feedback form explicitly asked “Why did you buy this
product?” or “Why didn’t you buy this product”. Students were
asked to relate their answers to the effectiveness of the branding
efforts. The feedback questionnaire was made available in the
virtual environment by clicking the “Feedback Questionnaire box”
in Second Life. Students were asked to fill out the feedback
questionnaire immediately upon completing the purchasing process. Student teams presented and argued for their chosen
branding strategies in a 15 e 20 minute presentation. During the
team presentations, teams had to explicitly motivate their
branding strategies and reflect on their effectiveness, through
peer-feedback and reflection of the course material. Professors
graded the course presentations on a 10-point scale using a uniform grading sheet. Creativity and innovation were evaluated
through discussion with all graders. Criteria for creativity and
innovation were agreed upon.
Individual participation was based on the quality and quantity of
contribution by the individual student. Students needed to attend
at least 12 out of 14 meetings to pass participation requirements. A
satisfactory mark for classroom participation was not obtained by
Fig. 2. Demographics.
223
participation in the discussion as such, but only if students could
demonstrate that they had studied and understood the required
literature. Both performance indicators were measured on a 10point scale, with 5.5 as the passing rate.
3.4. Procedures & course setting
The current study used an experimental set-up in the virtual
world of Second Life to facilitate an environment with realistic,
reflective, and contextualized activities, which could demonstrate
the use of both conceptual knowledge and procedural knowledge. In this 8-week Brand Management course of the international business degree program, students were randomly
assigned to small groups. Each group consisted of approximately
14 students, for a total of 155 students divided among 33 groups.
The groups of 14 were used for literature discussions and, from
these groups, students self-selected into teams of 4e5 students
for the Second Life assignment. Evidence showed this team size
yielded the highest group performance outcome (Lou, Abrami, &
D’Apollonia, 2001). The Second Life assignment required student
teams to develop, promote and eventually sell a product within
the virtual environment of Second Life. Three product types
(laundry care, pet care and baby care) in the fast moving consumer goods section were defined and student teams were
equally distributed amongst these categories. A healthy competition between student teams provided a closer simulation of
reality, with regard to competition that exists between companies in the workplace. (Pictures 3, 4, 5, & 6).
During the Second Life assignment, the learners collaboratively
developed their product. They also promoted their products via
YouTube-adds, flyers, posters, websites, Facebook communities, or
in some instances, dressed with their brand logo in class. Their
target population consisted of fellow students in the Brand management course, which also served as consumers of the various
products. Therefore, in week seven of the course, students were
individually given 20 Linden Dollars (online virtual money) to buy
products created by fellow students of the course. In week 8 of the
course, prior to the written exam, students had 48 consecutive
hours to sell their products to fellow students, the so-called
“shopping days”. To kick-off the shopping days, a live (face-toface) fair was organized. Students had two hours (face-to-face) to
convince fellow students to buy their products in the virtual
world. Students developed prototypes, flyers, and organized sales
pitches during this fair. To create more brand awareness, some
students displayed their logo or brand name via their attire, other
teams distributed flyers, or samples of their products. Following
the fair, promotion continued within the world of Second Life.
(Picture 7).
Technical support was provided with a helpdesk, which offered
both offline and online support. An extensive support website
provided all students with various manuals, guidelines, rules and
regulations, video tutorials, and important deadlines for the
project. The website also hosted graphics from the virtual world,
former student work samples, and the branding results depicted
by paper and TV-adds. Furthermore, to learn from previous experiences, a former student of the course served as a guest speaker
and entertained questions via voice chat with students in week
two of the course. The website and technical support resources
were made available at the beginning of the course. Upon
completion of their Second Life assignment, and prior to the final
exam, data collection was completed. In week eight an
announcement was posted in the course’s online learning platform and posted in Second Life, An invitation to participate in the
survey was posted in the course via a direct link to the online
survey. The introduction text to the survey clearly stated that all
224
Picture 3. One of the student teams efforts: Dogweiser, a beer for dogs.
data would be treated confidentially. Professors informed students
about the survey in their small groups and via an announcement
on the electronic learning environment (Blackboard). A reminder
was sent two days after the initial post. Participants had access to
the online survey for five days. Within that five-day period, 123
students successfully completed the survey, resulting in a
response rate of 79%. To analyze the impact of conceptual
knowledge and procedural knowledge on academic performance,
a regression analysis (OLS) was conducted. We measured the
impact of conceptual knowledge and procedural knowledge on
academic performance.
4. Results
4.1. Profile of participants
The mean age of participants was 21.61 years (SD ¼ 1.59),
with ages ranging from 19 to 30 years; 46% were male and 54%
225
Picture 4. A student teams branding efforts in the pet-care domain: vapoorize.
were female. The students were predominately European (86.5 %)
(German (53.2%), followed by Dutch (19.8%), other European nationality (13.5%)) followed by North American (6.3%), Asian
(5.4%), and South American (1.8%). Most students were in their
final year of undergraduate study (98.2%). The majority (64%)
of student participants completed this course as a program
requirement and followed a major in marketing, while
(23%) took this course as an elective with a minor in marketing
(Fig. 3).
4.2. Knowledge acquisition
4.2.1. Conceptual knowledge
Survey results showed 39% of students possessed conceptual
knowledge, as rated by their team members, while 61% were
rated by their peers as “not possessing conceptual knowledge”. If
the majority of peers rated them as experts, students were
categorized as possessing conceptual knowledge. In review of
constructs underlying conceptual knowledge, we found 37.4% of
226
Picture 5. Natural wash: washing nuts.
all students were considered general marketing experts, 35%
brand management experts, 30.1% advertising experts and 50.4%
were experts in conceptual product idea development. Students
were considered experts if the majority of peers rated them as
experts.
4.2.2. Procedural knowledge
In reference to procedural knowledge, 35.8% were rated by their
team members as possessing procedural knowledge. In review of
constructs underlying procedural knowledge, results indicated
30.1% were experts in designing products in Second Life; 29.3% of
all students were considered experts in building their shop in
Second Life; and 57.7% of all students were considered experts in
developing advertising strategies. In Second Life 32.5 % of all students who were experts in implementing advertising strategies,
whereas 61.8% excelled in implementing advertising strategy in
real life. Finally, 23.6% of all students were rated as experts in the
field of selling products in Second Life.
227
Picture 6. Competition amongst students within the baby-care domain.
4.2.3. Academic performance
To determine academic performance, we tested the reliability of
conceptual and procedure constructs and measurements. Both
constructs were reliable (Conceptual knowledge: a ¼ 0.83 and
Procedural knowledge a ¼ 0.68) (Hair, Black, Babin, & Anderson,
2009). The mean of conceptual knowledge and procedural knowledge was 0.48 (SD ¼ 0.25) and 0.47 (SD ¼ 0.21) respectively. The
average academic performance grade was 6.14 (SD ¼ 2.60); the final
course grade used a 10-point scale for measurement (Table 1).
As seen in Table 2, conceptual knowledge did not have a significant impact on academic performance (b 0.080; p ¼ 0.374).
Procedural knowledge, on the other hand, did have a positive affect
on academic performance (b 0.247; p ¼ 0.007) (Fig. 4).1
4.3. Teacher preparation & course design
4.3.1. Intentional pedagogy (knowledge-building pedagogy)
The design and implementation of this course focused on an
authentic learning experience in the context of a virtual world
1
We also tested for the interaction effect between procedural and conceptual
knowledge. The interaction term, reflecting the interaction between procedural
knowledge and conceptual knowledge was not significant.
(Second Life). This environment was used to support active
learning within the class through feedback from the environment
and peers, for reflection on knowledge gains. The intentional
design, in the virtual context for conceptual and procedural
knowledge, was a success given the student evaluation. An examination of survey results, on a 7-point Likert scale ranging
from totally disagree (1) to totally agree (7), indicated that students found “Second Life a nice way to apply their knowledge
gained during the course”(Mean 5.17; SD 1.70). They would rather
do the Second Life project than a written report (Mean 5.7; SD 1.76).
They enjoyed the Second Life project (Mean 5.33; SD 1.55), and they
would recommend doing the project again next year (Mean 5.55; SD
1.68). Further evidence is echoed directly in student comments
below:
The benefit of doing the Second Life project is that you bring the
theory, which you have learned during the course into practice.
You have to deal with all problems a real manager also faces. I
think this is very useful. The theory will be easier to recall and it
is a very fun project (Dutch, Male, age 20)
By doing the Second Life project, we learned a lot more than we
could possibly learn by writing a paper. For the first time (during
my whole academic career) I was able to transfer the theoretical
knowledge into practical uses. I really enjoyed doing the Second
228
Picture 7. Student fair.
Life project, the marketing campaign, and the real life fair! I
would definitely recommend this course to all future students,
as it is really a nice way to get a taste of how things are done in
real life. (Dutch, Female, age 20)
4.3.2. Technical support (digital literacy)
The virtual environment used in this study required students to
become proficient in the virtual world to complete course activities.
Therefore, in addition to conceptual knowledge for this brandmarketing course, it was necessary for learners to acquire the
digital literacy (Gilster, 1997) to complete the work. To support
students in this endeavor, learners were provided with several resources and support mechanisms at the onset of the project. Students were given Second Life manuals from the constructed course
website of the Second Life assignment and attended a mandatory
workshop provided by the instructor. This workshop addressed an
overview of the course, technology, and student expectations.
Furthermore, a Second Life helpdesk was implored, (both offline by
means of “open office hours” and online by means of a support
website and online helpdesk) to offer unlimited opportunities for
Q&A as students worked on the project and their own self-directed
learning process. Based on study results students utilized all resources and found them valuable. Second Life helpdesk support
was rated as sufficient (Mean 5.34; SD 1.57). Also most students
indicated they “Could manage to use Second Life in a few weeks”
(Mean 5.5; SD 1.33) Other questions found: “The manuals that were
provided were sufficient” (Mean: 5.45; SD 1.36), “The Second Life
workshop that was given was good” (Mean 4.73; SD 1.89) and “The
Second Life helpdesk answered my questions adequately” (Mean 4.44;
SD 2.13). Some of the students’ general remarks on the helpdesk
and technical support are noted below:
Fig. 3. Composition of final grade.
Table 1
Mean, SD, Cronbach alpha and correlation analysis
Variable
Mean SD
Alpha Procedural Conceptual Academic
knowledge knowledge performance
Procedural
0.467 0.250 0.680
knowledge
Conceptual
0.484 0.209 0.827
knowledge
Academic
6.138 2.603
performance
0.199*
0.263**
0.129
Notes: N ¼ 123 students. *p-value < 0.05 (two-tailed). ** p-value < 0.01 (two-tailed).
Table 2
Simple linear regression on academic performance.
Dependent variable
B
p
Conceptual knowledge
Procedural knowledge
R2
0.080
0.247
0.060*
0.347
0.007
Note: N ¼ 123, *p < 0.05.
Very good and clearly structured. You almost could find everything and it was always really nice and clearly explained. (Dutch,
Female, age 22)
Most data regarding the helpdesk pertained to media uploads in
Second Life (such as audio and/or video files or YouTube links).
Most of the general remarks included a technical aspect that hindered them in using the full potential of Second Life. Examples of
technical issues were ‘slow laptops’, ‘bad Internet connections’ or
‘problems installing Second Life’. The aspect of time management
was also referred to often, even in combination with the technical
issues.
Mainly computer issues, crashes and bad connections, otherwise everything was surprisingly clear and well structured,
thumbs up! (Dutch, Male, age 21)
Access to Second Life. My laptop is quite old so it was really
difficult to login to Second Life and even in Second Life it was
most of the time slow motion. (German, Male, age 23)
4.3.3. Time management
As in real life, students had to manage multiple priorities and
encountered an environment that necessitated work in various
modes. The course was intentionally designed to split time
229
between face-to-face team meetings, lecture-based class sessions,
the virtual environment (Second Life), and via virtual support resources and collaborative spaces. Therefore, the instructor had to
enable a learning environment that allowed for adequate time to
learn, engage, and apply throughout these various modalities. The
course structure supported the division of time/modality as such:
(20% tutorial groups, 10%, lectures, 70% Self-study and Second Life
project). The time allocations and workload were considered
appropriate by students (Mean: 4.99; SD: 1.67). However, technical issues were considered a hindrance to student effectiveness
and jeopardized efficient time management, as student quotes
echo:
Everything happened pretty fast, so sometimes I had problems
keeping track of what we had to do by when. But the emails
were helpful, as were the Second Life workshops, and the list of
deadlines in the block book. (North American Female, age 22)
Time pressure due to other courses e problems with installing
the software (but I managed, the graphic card was too old)
(German, Female, age 23)
4.3.4. Assessment and evaluation
Authentic assessment, with a variety of feedback sources, was
used throughout the Second Life project. Assessment and evaluation included the following: Final exam (5-question written essay),
performance indicators (sales revenue, peer feedback, argumentation for branding strategies & creativity and innovativeness) and
individual participation in class. When asked about the Second Life
project compared to a traditional report, students commented.
I believe Second Life, together with the marketing activities we
did in real life, provides a surrounding that’s very close to what a
real brand manager would face. If everything were only in theory,
we wouldn’t face the same challenges. (German, Male, age 23)
I think the Second Life project offers a new opportunity in terms
of learning. It is a creative tool, where everybody can express his
abilities and skills. I think in a paper it is really difficult to
express ideas and feelings towards a certain product. (German,
Male, age 23)
4.4. Room for improvement, transferability to other domains &
limitations of Second Life as an educational tool
Students were asked to identify areas for course improvement
and to offer suggestions to improve the Second Life course aspect.
Student comments were positive, with a strong appreciation for the
practical aspects of the course and the innovative approach of using
Second Life:
Thank you for offering a unique learning experience! Many of
my friends back home are impressed by the “outside of the box”
education. (German, Male, age 23)
Even though, I am new to this field I really enjoyed this course,
mostly because of the practical aspect, which is not given often.
Fig. 4. Conceptual model showing the impact of procedural knowledge on academic
performance.
When asked for feedback on course teachers/instructors, students were positive and emphasized the enthusiasm and involvement of teaching staff. Students also indicated the need for teacher
awareness and expertise related to the technicalities of the program (Second Life) and its use in class. Survey results showed that
students perceived a relatively equal distribution of the workload
230
among team members though (Mean: 4.48; SD: 2.12), but also
highlighted the issue of ‘social loafing’ in teamwork.
Tutors can’t control who did the job and who didn’t. Obviously it
is teamwork, but how do they know who did most part of the
job? (Asian, Female, age 21)
Instruct the tutors how to use Second Life, so they can answer
questions students have about it. (Dutch, Male, age 20)
Tutorials should cover more useful tips for Second Life. (Female,
German, age 21)
demonstrate expertise in the course concepts and underlying
processes. The resemblance to real life and reflection of action is
one of the key benefits of Second Life use in the current study. The
development of procedural skills increases academic performance
and prepares the learner to successfully apply those skills in the
workplace (Beaudry et al., 2013; Friedman, 2005; Pink, 2006). By
implementing virtual worlds in education, universities not only
prepare students for their future jobs, with insight into the
complexity of industry (IBM, 2010; Johnson et al., 2013), they also
position their institution to deliver well equipped graduates.
5.2. Implications for educators
Students were explicitly asked about the limitations of Second
Life as an educational tool and how it could be used more effectively in the future. The “addictiveness” of the environment is often
mentioned as a limiting factor of Second Life, as some students
indicated a “loss of themselves” when immersed in Second Life,
spending too much time online, dealing with small details. The
concept of free-riding or social loafing and work distribution was
also mentioned. Recommendations focused predominantly on two
aspects: Time management and aquiantance with Second Life.
When counting the suggestions on the possibility to implement
Second Life in other courses, 42.1% indicated no other possible
application of Second Life in education, 31.4% suggested integration
in marketing-related courses, 11.6% saw multiple domains where
Second Life could be integrated, other domains indicated by students included: Entrepreneurship/Business plan (4.9%), supply
chain management (4.1%), strategy (2.5%), art (2.5%). Other possible
domains mentioned included: finance, consumer behavior and
HRM (6.6%). A common remark was that Second Life was especially
suited for creative courses/domains.
In Second Life, it was easy drifting off from reality. (German,
Female, age 23)
People might get distracted and do "nonsense" in Second Life
5. Discussion
The objective of this study was to disentangle and analyze the
impact of conceptual knowledge and procedural knowledge on
academic performance, and to discuss resulting implications for
using the virtual environment as the context to apply both. Results
of the regression analysis show that conceptual knowledge does
not influence academic performance, whereas procedural knowledge does have a positive influence on academic performance.
Executing this research in the setting of a virtual environment
made it possible to disentangle both concepts, and to analyze their
effects in isolation. The results offer opportunities for educators to
engage learners in active learning mediated by virtual worlds. This
research provides guidance for education of the future that will
include not only conceptual knowledge, but also the application
and practice of procedural knowledge in simulated context. Offering education in a virtual world creates a context, which brings
knowledge into practice and serves as an accelerator for academic
performance.
5.1. Implications
The results from this study show that students enjoy using
Second Life in education and prefer to demonstrate their knowledge through this mediated learning approach over traditional
forms of assessment, such as research papers and reports. Students
indicate a positive response to the integration of Second Life and
Teacher beliefs influence the way educators approach their
students, how they interpret information (Oosterheert & Vermunt,
2001; Richardson, 1996; Tillema, 1994) and their method of
teaching and curricula design (Clark & Peterson, 1986; Shavelson,
1973; Shavelson & Stern, 1981; Shulman, 1986, 1987). This influences pedagogical decisions and strategies with regard to representing their subject matter to their students (Fernández-Balboa
& Stiehl, 1995). The current research demonstrates the value of
using virtual worlds to apply procedural knowledge, and the positive impact it has on academic performance. When implementing
virtual worlds in education, the considerations below can be taken
into account. While this study focused on a brand management
course, these considerations are applicable and generalizable to all
educators in higher education, regardless of domain, discipline or
field.
5.2.1. Technicalities
As the movement towards online learning becomes more
prevalent, teachers should consider innovative ways to implement
their teaching in these promising technologies (Clift et al., 2001;
Niess, 2005; Oblinger & Oblinger, 2005), instead of just moving
content online (Lohr, 2009; Niess, 2005; Wang, 2009). Bringing real
world experience into the classroom by means of virtual worlds
requires a learning curve in technology use and curricular design
for teachers, as they might not be fully equipped for this change
(Allen & Seaman, 2007; Blin & Munro, 2008). Therefore, training
and development programs for educators can also emphasize on
the development of tool-related, task-related (Kaptelinin & Nardi,
2006) and meta-functional competencies (Kaptelinin & Nardi,
2006) in the context of emerging technologies (Blin & Munro,
2008). When using virtual worlds (such as Second Life) in education, our results indicate the need for educators to develop an understanding of these emerging technologies, in order to engage
with students and observe their work in these environments.
Technical support in the form of trainings, workshops, manuals and
support are a first step in facilitating this development. Minimum
hardware specifications (internet speed, application downloads,
processor speed) should also be clearly communicated and available on university computers. Both technical support and hardware
requirements are also applicable to students, and support is needed
to aid in their learning curve as they advance their digital literacy
with a particular tool.
5.2.2. Course preparation
Implementing virtual worlds in the classroom requires adequate
course preparation due to the dynamic nature of virtual worlds.
Managing students’ expectations by means of clear guidelines is
crucial in avoiding future disputes. Peer feedback and team member evaluations are essential to assess the equal contribution of all
team members. Concerning time allocation, it is advisable to offer a
clear determination on how time will be used, and split by modality
(i.e. face-to-face class-time, vs. self-study time vs. group work, etc.).
Due to the immersive environment, described as “addictive” by
some students, it is important to explicate the division between
offline and online activities and to indicate the expected time
allocation for both.
5.2.3. Evaluation & assessment
Given the complexity of the task, and the effort required to
measure both conceptual and procedural knowledge, a variety of
assessments are recommended. Such measures may include feedback from multiple sources (e.g. teachers, peers, industry experts,
external partners). An authentic assessment plan, which evaluates
both individual and group work, needs to be set up before the
course and explicitly communicated to students. Guidelines for
grading should be transparent, so students know what is expected
of them and how to successfully achieve desired learning
outcomes.
6. Limitations
The following limitations should be considered when interpreting the results. First, the learning activity was obligatory
within an international business program, which implies that a
majority of students had at least some basic understanding of
marketing or branding. To execute the same experiment in a
setting with real novices in the field of marketing or branding, the
results of this research may be strengthened and potentially increase the effects of both types of knowledge. Secondly, within
this experiment knowledge was measured at the end of the course
to allow students to get acquainted with each other and with the
technology.
Third, as competing theories regarding the developmental relations between conceptual and procedural knowledge suggest
(Rittle-Johnson et al., 2001), there might be a possibility of bidirectional causal links between conceptual and procedural knowledge. Longitudinal research is needed to examine whether
procedural knowledge and conceptual knowledge interact over
time and whether they could strengthen the results of this study.
Fourth, there are some limitations concerning the sample used. A
more conclusive result could be achieved with a larger sample.
Finally, when relating to the instrument, other measurements
could be used to analyze the concepts of conceptual knowledge or
procedural knowledge.
7. Implications for further research
In order to strengthen the results of this research, the measurement should be repeated in a different setting (e.g. different
domain of content), and should involve students with a multidisciplinary background. Such changes might strengthen results, as
the variation in the level of expertise will be larger. When repeating
the experiment, multiple measurements can be taken throughout
the experiment to measure the development of both types of
knowledge. Further research might focus on the transferability effect of increased procedural knowledge on the labor market.
Studies should investigate the long-term effects of redesigning
curricula by means of implementing virtual worlds to increase
conceptual and procedural knowledge. Furthermore, research is
needed to identify strategies, methods, and programs, which support educators and instructional designers in the development of
such mediated learning approaches.
8. Conclusion
The present study analyzes the role of conceptual knowledge
and procedural knowledge on students’ academic performance,
231
and provides a new perspective on the relationship between conceptual knowledge, procedural knowledge and academic performance, particularly in virtual worlds. Results confirm the
importance of procedural knowledge to academic performance
and, thus, to students’ achieved educational goals. Such evidence
can guide course design toward strategies that engage both conceptual knowledge and procedural knowledge. Thereby, showing
that virtual worlds can serve as an accelerator and identifier for
developing procedural knowledge. With a research setting in the
virtual environment that resembles real life, solving real world
problems, students are equipped with a solid preparation for the
dynamic workplace. Thereby, the research findings challenge educators to become familiar with emerging technologies, such as
virtual worlds, as a means of bringing real life practice into the
classroom. In summary, universities and educators have the opportunity to engage learners and support the application of conceptual and procedural knowledge by using virtual worlds. In doing
so, they equip learners with an improved opportunity to shape
their future in the labor market, for which they are better prepared.
Acknowledgments
We are grateful to G.R.H. Westenberg for creating and designing
the visual content of this manuscript. We are also grateful to an
anonymous reviewer for his sharp comments and feedback on
previous versions of this manuscript.
References
Alexander, P. A., Schallert, D. L., & Hare, V. C. (1991). Coming to terms: how researchers in learning and literacy talk about knowledge. Review of Educational
Research, 61(3), 315e343.
Allen, I. E., & Seaman, J. (2007). Online nation: Five years of growth in online learning.
The Sloan Consortium.
Anderson, J. R. (1993). Rules of the mind. Routledge.
Anderson, J. R. (1995). Learning and memory: An integrated approach. New York:
John Wiley & Sons.
Atallah, H. E., Lopez-Paniagua, D., Rudy, J. W., & O’Reilly, R. C. (2007). Separate
neural substrates for skill learning and performance in the ventral and dorsal
striatum. Nature Neuroscience, 10(1), 126e131. http://dx.doi.org/10.1038/nn1817.
Ayers, D. J., & Underwood, R. L. (2007). Integrating concepts across marketing
courses via experiential learning. Journal for Advancement of Marketing Education, 11(2), 63e68.
Barber, M., Donnelly, K., & Rizvi, S. (2013). An avalenche is coming: Higher education and the revolution ahead.
Baroody, A. J. (2003). The development of adaptive expertise and flexibility: the
integration of conceptual and procedural knowledge. The Development of
Arithmetic Concepts and Skills: Constructing Adaptive Expertise, 1e33.
Baroody, A. J., Feil, Y., & Johnson, A. R. (2007). An alternative reconceptualization of
procedural and conceptual knowledge. Journal for Research in Mathematics
Education, 38(2), 115e131.
Beaudry, P., Green, D. A., & Sand, B. M. (2013). The great reversal in the demand for
skill and cognitive tasks. National Bureau of Economic Research.
Belei, N., Noteborn, G., & de Ruyter, K. (2011). It’s a brand new world: teaching
brand management in virtual environments. Journal of Brand Management.
http://dx.doi.org/10.1057/bm.2011.6.
Bell, M. W. (2008). Toward a definition of “virtual worlds.” Journal of Virtual Worlds
Research, 1, 2e5.
Bell, R. L., & Trundle, K. C. (2008). The use of a computer simulation to promote
scientific conceptions of moon phases. Journal of Research in Science Teaching,
45(3), 346e372. http://dx.doi.org/10.1002/tea.20227.
Bisanz, J., & LeFevre, J.-A. (1992). Understanding elementary mathematics. In
J. I. D. Campbell (Ed.), The nature and origins of mathematical skills (Vol. 91; pp.
113e136). Oxford, England: North-Holland. http://dx.doi.org/10.1016/S01664115(08)60885-7.
Blin, F., & Munro, M. (2008). Why hasn’t technology disrupted academics’ teaching
practices? Understanding resistance to change through the lens of activity
theory. Computers & Education, 50(2), 475e490. http://dx.doi.org/10.1016/
j.compedu.2007.09.017.
Bluestone, C. (2000). Feature films as a teaching tool. College Teaching, 48(4), 141e146.
Bluestone, C. (2007). Infusing active learning into the research methods unit. College
Teaching, 55(3), 91e95.
Bolt, M. A., Killough, L. N., & Koh, H. C. (2001). Testing the interaction effects of task
complexity in computer training using the social cognitive model. Decision
Sciences, 32(1), 1e20. http://dx.doi.org/10.1111/j.1540-5915.2001.tb00951.x.
232
Boyatzis, R. E., Stubbs, E. C., & Taylor, S. N. (2002). Learning cognitive and emotional
intelligence competencies through graduate management education. Academy
of Management Learning & Education, 1(2), 150e162.
Briars, D., & Siegler, R. S. (1984). A featural analysis of preschoolers’ counting
knowledge. Developmental Psychology, 20(4), 607.
Brooks, B. W., Burson, T. E., & Rudd, D. V. (2006). Addressing current research gaps
and directions in educational marketing simulations. Journal for Advancement of
Marketing Education, 9, 43e49.
Budd, K., Carson, E., Garelick, B., Klein, D., Milgram, R. J., Raimi, R. A., & Wilson, W. S.
(2005). Ten myths about math education and why you shouldn’t believe them.
Retrieved from http://www.nychold.com/myths-050504.html.
Burbules, N. C., & Callister, T. A. J. (2000). Universities in transition: the promise and
the challenge of new technologies. Teachers College Record, 102(2), 271e293.
http://dx.doi.org/10.1111/0161-4681.00056.
Byrnes, J. P., & Wasik, B. A. (1991). Role of conceptual knowledge in mathematical
procedural learning. Developmental Psychology, 27(5), 777.
Candy, P. (2000). Learning and earning: graduate skills for an uncertain future. In
Proceedings, international life long learning conference.
Cannon-Bowers, J. A., Bowers, C. A., & Sanchez, A. (2008). Using synthetic learning
environments to train teams. In V. I. Sessa, & M. London (Eds.), Work group
learning (pp. 318e327). New York, NJ: Lawrence Earlbaum Associates.
Çepni, S., Taş, E., & Köse, S. (2006). The effects of computer-assisted material on
students’ cognitive levels, misconceptions and attitudes towards science.
Computers
&
Education,
46(2), 192e205.
http://dx.doi.org/10.1016/
j.compedu.2004.07.008.
Christensen, C. M., & Eyring, H. J. (2011). The innovative university. Changing the DNA
of higher education from the inside out. San Francisco, CA: Jossey-Bass.
Christian, W. (2008). Learning experience with virtual worlds. Journal of Information
Systems Education, 19, 263e266.
Clark, C. M., & Peterson, P. L. (1986). Teacher’s though process. In M. C. Wittrock
(Ed.), Handbook of research on teaching (pp. 255e296). New York: Macmillian.
Claxton, G., Lucas, B., & Webster, R. (2010). Bodies of knowledge: How the learning
sciences could transform practical and vocational education. London.
Clift, R. T., Mullen, L., Levin, J., & Larson, A. (2001). Technologies in contexts: implications for teacher education. Teaching and Teacher Education, 17(1), 33e50.
http://dx.doi.org/10.1016/S0742-051X(00)00037-8.
Crawford, C. (2011). The art of computer game design. Berkeley, CA: McGrawHill.
De Freitas, S. (2006). Using games and simulations for supporting learning.
Learning, Media and Technology, 31(4), 343e358. http://dx.doi.org/10.1080/
17439880601021967.
De Freitas, S., & Neumann, T. (2009). The use of “exploratory learning” for supporting immersive learning in virtual environments. Computers & Education,
52(2), 343e352. http://dx.doi.org/10.1016/j.compedu.2008.09.010.
De Freitas, S., & Oliver, M. (2006). How can exploratory learning with games and
simulations within the curriculum be most effectively evaluated? Computers &
Education, 46(3), 249e264.
De Jong, T., & Ferguson-Hessler, M. G. M. (1996). Types and qualities of knowledge.
Educational Psychologist, 31(2), 105e113.
Dede, C. (2009). Immersive interfaces for engagement and learning. Science,
323(5910), 66e69. http://dx.doi.org/10.1126/science.1167311.
Donnelly, K. (2010). A second chance for second life? Training Journal, 43e46.
Drake-Bridges, E., Strelzoff, A., & Sulbaran, T. (2011). Teaching marketing through
a micro-economy in virtual reality. Journal of Marketing Education, 33(3), 295e
311.
Drea, J. T., Tripp, C., & Stuenkel, K. (2005). An assessment of the effectiveness of an
in-class game on marketing students’ perceptions and learning outcomes.
Marketing Education Review, 15(1), 25e33.
Elam, E. L. R., & Spotts, H. E. (2004). Achieving marketing curriculum integration: a
live case study approach. Journal of Marketing Education, 26(1), 50e65.
European Centre for the Development of Vocational Training. (2010). Skills supply
and demand in Europe. Medium-term forecast up to 2020. Luxembourg.
Fernández-Balboa, J.-M., & Stiehl, J. (1995). The generic nature of pedagogical
content knowledge among college professors. Teaching and Teacher Education,
11(3), 293e306. http://dx.doi.org/10.1016/0742-051X(94)00030-A.
Fink, L. D., & Fink, A. K. (Eds.). (2009). Designing courses for significant learning:
Voices of experience. Teaching theology & religion (Vol. 14). San Francisco: JosseyBass.
Frenk, J., Chen, L., Bhutta, Z. A., Cohen, J., Crisp, N., Evans, T., & Zurayk, H. (2010).
Health professionals for a new century: transforming education to strengthen
health systems in an interdependent world. Lancet, 376(9756), 1923e1958.
http://dx.doi.org/10.1016/S0140-6736(10)61854-5.
Friedman, T. L. (2005). The world is flat: A brief history of the twenty-first century.
World (Vol. 5). New York: Farrar, Straus, and Giroux.
Frye, D., Braisby, N., Lowe, J., Maroudas, C., & Nicholls, J. (1989). Young children’s
understanding of counting and cardinality. Child Development, 1158e1171.
Gallistel, C. R., & Gelman, R. (1978). The child’s understanding of number. Cambridge,
MA: Harvard University Press.
Galvão, J. R., Martins, P. G., & Gomes, M. R. (2000). Modeling reality with simulation
games for a cooperative learning. In Proceedings of the 32nd conference on
Winter simulation (pp. 1692e1698). San Diego, CA, USA: Society for Computer
Simulation International. Retrieved from http://dl.acm.org/citation.cfm?
id¼510378.510626.
Gelman, R., & Meck, E. (1983). Preschoolers’ counting: principles before skill.
Cognition, 13(3), 343e359.
Gijselaers, W. H., & Milter, R. G. (2009). The challenge of change in business economics education: lessons learned from the EDiNEB Network. In R. De Filippi, &
Wankel (Eds.), Being and becoming a management education scholar. Research in
management education and development (pp. 153e170). Greenwich, Con: Information Age Publishing Inc.
Gijselaers, W. H., & Milter, R. G. (2010). Issues in accounting/business education. In
P. Peterson, B.E., & B. McGaw (Eds.), International encyclopedia of education (pp.
39e44). Oxford: Elsevier.
Gijselaers, W. H., & Schmidt, H. G. (1995). Effects of quantity of instruction on time
spent on learning and achievement. Educational Research and Evaluation, 1(2),
183e201. http://dx.doi.org/10.1080/1380361950010204.
Gilster, P. (1997). Digital literacy. New York: Wiley.
Graeff, T. R. (2010). Strategic teaching for active learning. Marketing Education Review, 20(3), 265e278. http://dx.doi.org/10.2753/MER1052-8008200307.
Green, C. S., & Bavelier, D. (2003). Action video game modifies visual selective
attention. Nature, 423(6939), 534e537.
Greeno, J. G. (1978). Understanding and procedural knowledge in mathematics
instruction 1. Educational Psychologist, 12(3), 262e283.
Greeno, J. G., Riley, M. S., & Gelman, R. (1984). Conceptual competence and children’s counting. Cognitive Psychology, 16(1), 94e143.
Hair, J. F. J., Black, W. C., Babin, B. J., & Anderson, R. E. (2009). Multivariate data
analysis (7th ed.). Prentice Hall.
Harasim, L. (2012). Learning theory and online technologies. New York, NJ: Routledge.
Haytko, D. L. (2006). The price is right: an experiential pricing concepts game.
Marketing Education Review, 16(2), 1.
Heinecke, W. F., Milman, N. B., Washington, L. A., & Blasi, L. (2002). New directions
in the evaluation of the effectiveness of educational technology. Computers in
the Schools, 18(2e3), 97e110.
Honebein, P. C., Duffy, T. M., & Fishman, B. J. (1993). Constructivism and the
design of learning environments: context and authentic activities for
learning. In T. M. Duffy, J. Lowyck, & D. H. Jonassen (Eds.), Designing environments for constructive learning (Vol. 105; pp. 87e108). New York: Springer
Verlag.
Hornik, S., & Thornburg, S. (2010). Really engaging accounting: second lifeTM as a
learning platform. Issues in Accounting Education, 25(3), 361e378.
IBM. (2010). Capitalizing on complexity: Insights from the global chief executive officer
study.
Imeokparia, P. O., & Kennedy, E. (2013). Stress management: an approach to
ensuring high academic performance of business education students. European
Journal of Educational Studies, 5, 167e176.
Jensen, E. J., & Owen, A. L. (2001). Pedagogy, gender, and interest in economics. The
Journal of Economic Education, 32(4), 323e343.
Johnson, L., Adams, S., Cummins, M., Estrada, V., Freeman, A., & Ludgate, H. (2013).
The NMC horizon report: 2013 higher education edition. Austin, TX.
Kanes, C. (2011). In C. Kanes (Ed.), Elaborating professionalism. Studies in practice and
theory. Dordrecht, Boston, London: Springer Science.
Kaptelinin, V., & Nardi, B. A. (2006). Acting with technology: Activity theory and
interaction design. Cambridge, MA: MIT Press.
Karmiloff-Smith, A. (1994). Self-organization and cognitive change. In
M. H. Johnson, Y. Munakata, & R. O. Gilmore (Eds.), Brain development and
cognition (pp. 592e618). Cambridge MA: Blackwell Publishing.
Kozinets, R. V., & Kedzior, R. (2009). I, avatar auto-netnographic research in virtual
worlds. Virtual Social Identity and Social Behaviour, 3, 19.
Kozlowski, S. W. J., & Bell, B. (2007). A theory-based approach for designing
distributed learning systems. In S. M. Fiore, & E. Salas (Eds.), Toward a science of
distributed learning (pp. 15e39). Washington, DC: American Psychological
Association.
Laveñe, D. A. (2006). In-class active cooperative learning: A way to build knowledge
and skills in marketing courses.
LeFevre, J.-A., Smith-Chant, B. L., Fast, L., Skwarchuk, S.-L., Sargla, E., Arnup, J. S., &
Kamawar, D. (2006). What counts as knowing? The development of conceptual
and procedural knowledge of counting from kindergarten through grade 2.
Journal of Experimental Child Psychology, 93(4), 285e303.
Lerchner, A., La Camera, G., & Richmond, B. (2007). Knowing without doing. Nature
Neuroscience, 10(1), 15e17.
Levin, M. A., & Davis, D. F. (2007). Virtual “third places” and experiential learning: a
case study of blogging in a marketing promotions course. Journal of Advancement of Marketing Education, 10, 18e26.
Lohr, S. (2009). Study finds that online education beats the classroom [online article
on The New York Times]. Retrieved from http://bits.blogs.nytimes.com/2009/
08/19/study-finds-that-online-education-beats-the-classroom/.
Lou, Y., Abrami, P. C., & D’Apollonia, S. (2001). Small group and individual learning
with technology: a meta-analysis. Review of Educational Research, 71(3), 449e
521. http://dx.doi.org/10.3102/00346543071003449.
Lucas, B., & Claxton, G. (2009). Wider skills for learning: What are they, how can they
be cultivated, how could they be measured and why are they important for
innovation. London.
Maher, J. K., & Hughner, R. S. (2005). Experiential marketing projects: student
perceptions of live case and simulation methods. Journal for Advancement of
Marketing Education, 7, 1e10.
Mayo, M. J. (2009). Video games: a route to large-scale STEM education? Science,
323(5910), 79e82. http://dx.doi.org/10.1126/science.1166900.
Means, B., & Haertel, G. D. (2004). Using technology evaluation to enhance student
learning. New York: Teachers College Press.
Messinger, P. R., Stroulia, E., Lyons, K., Bone, M., Niu, R. H., Smirnov, K., & Perelgut, S.
(2009). Virtual worldsdpast, present, and future: new directions in social
computing. Decision Support Systems, 47(3), 204e228.
Murthy, N. N., Challagalla, G. N., Vincent, L. H., & Shervani, T. A. (2008). The impact
of simulation training on call center agent performance: a field-based investigation. Management Science, 54(2), 384e399. http://dx.doi.org/10.1287/
mnsc.1070.0818.
Myers, S. D. (2010). Experiential learning and consumer behavior: an exercise in
consumer decision making. Journal for Advancement of Marketing Education,
17(1), 23e26.
Nelson, B. C., & Erlandson, B. E. (2012). Designing for learning in virtual worlds:
Interdisciplinary approaches to education in technology. New York, NJ:
Routledge.
Nelson, B. C., Ketelhut, D. J., Clarke, J., Bowman, C., & Dede, C. (2005). Design-based
research strategies for developing a scientific inquiry curriculum in a multi-user
virtual environment. Educational Technology, 45(1), 21e27.
Neulight, N., Kafai, Y. B., Kao, L., Foley, B., & Galas, C. (2006). Children’s participation
in a virtual epidemic in the science classroom: making connections to natural
infectious diseases. Journal of Science Education and Technology, 16(1), 47e58.
http://dx.doi.org/10.1007/s10956-006-9029-z.
Niess, M. L. (2005). Preparing teachers to teach science and mathematics with technology: developing a technology pedagogical content knowledge. Teaching and
Teacher Education, 21(5), 509e523. http://dx.doi.org/10.1016/j.tate.2005.03.006.
Noteborn, G., Bohle Carbonell, K., Dailey-Hebert, A., & Gijselaers, W. (2012). The role
of emotions and task significance in virtual education. The Internet and Higher
Education. http://dx.doi.org/10.1016/j.iheduc.2012.03.002.
Oblinger, D., & Oblinger, J. (2005). Retrieved from. In D. Oblinger, & J. Oblinger
(Eds.), Is it age or IT: first steps towards understanding the net generation (pp.
2.1e2.20). Boulder, CO: EDUCAUSE http://net.educause.edu/ir/library/pdf/
pub7101.pdf.
Oosterheert, I. E., & Vermunt, J. D. (2001). Individual differences in learning to
teach: relating cognition, regulation and affect. Learning and Instruction, 11(2),
133e156. http://dx.doi.org/10.1016/S0959-4752(00)00019-0.
Page, D., & Mukherjee, A. (2007). Promoting critical-thinking skills by using negotiation exercises. Journal of Education for Business, 82(5), 251e257. http://
dx.doi.org/10.3200/JOEB.82.5.251-257.
Parush, A., Hamm, H., & Shtub, A. (2002). Learning histories in simulation-based
teaching: the effects on self-learning and transfer. Computers & Education,
39(4), 319e332. http://dx.doi.org/10.1016/S0360-1315(02)00043-X.
Pena, A., & Antonio, A. De. (2010). Inferring interaction to support collaborative
learning in 3D virtual environments through the user’s avatar non-verbal
communication. International Journal of Technology Enhanced Learning, 2(1/2),
75. http://dx.doi.org/10.1504/IJTEL.2010.031261.
Pesek, D. D., & Kirshner, D. (2000). Interference of instrumental instruction in
subsequent relational learning. Journal for Research in Mathematics Education,
524e540.
Petraglia, J. (1998). Reality by design: The rhetoric and technology of authenticity in
education. Mahwah, NJ: Lawrence Erlbaum Associates.
Piaget, J. (2013). Success and understanding. Cambridge, MA: Harvard University
Press.
Pink, D. H. (2006). A whole new mind: Why right-brainers will rule the future. New
York: Riverhead Trade (Paperbacks).
Prince, M. (2004). Does active learning work? A review of the research. Journal of
Engineering Education, 93(3), 223e231. http://dx.doi.org/10.1002/j.21689830.2004.tb00809.x.
Renken, M. D., & Nunez, N. (2013). Computer simulations and clear observations do
not guarantee conceptual understanding. Learning and Instruction, 23, 10e23.
http://dx.doi.org/10.1016/j.learninstruc.2012.08.006.
Richardson, V. (1996). The role of attitudes and beliefs in learning to teach. In
J. Sikula (Ed.), Handbook of research on teacher education (Vol. 2; pp. 102e119).
New York: Macmillian.
Rittle-Johnson, B., & Siegler, R. S. (1998). The relation between conceptual and
procedural knowledge in learning mathematics: a review.
Rittle-Johnson, B., Siegler, R. S., & Alibali, M. W. (2001). Developing conceptual
understanding and procedural skill in mathematics: an iterative process. Journal of Educational Psychology, 93(2), 346.
Roberts, R., Gott, R., & Glaesser, J. (2010). Students’ approaches to open-ended science investigation: the importance of substantive and procedural understanding. Research Papers in Education, 25(4), 377e407. http://dx.doi.org/
10.1080/02671520902980680.
Rutten, N., van Joolingen, W. R., & van der Veen, J. T. (2012). The learning effects of
computer simulations in science education. Computers & Education, 58(1), 136e
153. http://dx.doi.org/10.1016/j.compedu.2011.07.017.
Salas, E., & Rosen, M. A. (2010). Experts at work: principles for developing expertise
in organizations. In S. W. J. Kozlowski, & E. Salas (Eds.), Learning, training, and
development in organizations. New York, NJ: Routledge.
Salmon, G. (2009). The future for (second) life and learning. British Journal of
Educational Technology, 40(3), 526e538.
Sauvé, L., Renaud, L., Kaufman, D., & Marquis, J. S. (2007). Distinguishing between
games and simulation: a systematic review. Journal of Educational Technology
and Society, 10(3), 247.
Scardamalia, M., & Bereiter, C. (2003). Knowledge building environments: extending the limits of the possible in education and knowledge work. In A. DiStefano,
K. E. Rudestam, & R. Silverman (Eds.), Ecyclopedia of distributed learning (pp. 1e
10). Thousand Oaks: Sage Publications.
233
Scardamalia, M., & Bereiter, C. (2006). Knowledge building: theory, pedagogy, and
technology. In R. K. Sawyer (Ed.), Cambridge handbook of the learning sciences
(pp. 97e118). New York: Cambridge University Press.
Schank, R. C. (2011). Making minds less well educated than our own. Routledge.
Schee, B. A. V. (2007). Setting the stage for active learning: an interactive marketing
class activity. Marketing Education Review, 17(1), 63.
Schiller, S. Z., Goodrich, K., & Gupta, P. B. (2013). Let them play! Active learning in a
virtual world. Information Systems Management, 30(1), 50e62.
Schneider, M., & Stern, E. (2005). Conceptual and procedural knowledge of a
mathematics problem: their measurement and their causal interrelations. In
Proceedings of the 27th annual conference of the cognitive science society.
Sevilla, M. (2012). Problem based learning in the 21st century. CreateSpace Independent Publishing Platform.
Shavelson, R. J. (1973). What is the basic teaching skill? Journal of Teacher Education,
24(2), 144e151.
Shavelson, R. J., & Stern, P. (1981). Research on teachers’ pedagogical thoughts,
judgments, decisions, and behavior. Review of Educational Research, 51(4), 455e
498. http://dx.doi.org/10.3102/00346543051004455.
Shulman, L. S. (1986). Those who understand: knowledge growth in teaching.
Educational Researcher, 15(2), 4e14.
Shulman, L. S. (1987). Knowledge and teaching: foundations of the new reform.
Harvard Educational Review, 57(1), 1e23.
Star, J. R. (2005). Reconceptualizing procedural knowledge. Journal for Research in
Mathematics Education, 404e411.
Star, J. R. (2007). Foregrounding procedural knowledge. Journal for Research in
Mathematics Education, 132e135.
Thackray, L., Good, J., & Howland, K. (2010). Learning and teaching in virtual worlds:
boundaries, challenges and opportunities. In Researching learning in virtual
worlds (pp. 139e158). Springer.
Tillema, H. H. (1994). Training and professional expertise: bridging the gap between
new information and pre-existing beliefs of teachers. Teaching and Teacher
Education, 10(6), 601e615. http://dx.doi.org/10.1016/0742-051X(94)90029-9.
Tuten, T. (2009). Real world experience, virtual world environment: the design and
execution of marketing plans in second life. Marketing Education Review, 19(1),
1e5.
Urban-Woldron, H. (2009). Interactive simulations for the effective learning of
physics. Journal of Computers in Mathematics and Science Teaching, 28(2), 163e
176.
Van Berkum, J. J., & de Jong, T. (1991). Instructional environments for simulations.
Education and Computing, 6(3), 305e358.
Van Zundert, M., Sluijsmans, D., & van Merriënboer, J. (2010). Effective peer assessment processes: research findings and future directions. Learning and Instruction,
20(4), 270e279. http://dx.doi.org/10.1016/j.learninstruc.2009.08.004.
Wang, T. (2009). Rethinking teaching with information and communication technologies (ICTs) in architectural education. Teaching and Teacher Education, 25(8),
1132e1140. http://dx.doi.org/10.1016/j.tate.2009.04.007.
Warburton, S. (2009). Second life in higher education: assessing the potential for
and the barriers to deploying virtual worlds in learning and teaching. British
Journal of Educational Technology, 40(3), 414e426.
Ward, A., Stoker, H., & Murray-Ward, M. (1996). Achievement and ability testsdefinition of the domain. In Educational measurement: Theories and application (pp. 2e5). University Press of America.
Ward, J. (2010). The avatar lecturer: learning and teaching in second life. Marketing
Intelligence & Planning, 28(7), 862e881.
Wheeler, R. (2008). Experiential learning: impact of two instructional methods on
student-instructor interaction, student critical thinking, and student course
evaluations. Journal for Advancement of Marketing Education, 12, 63e78.
Wood, N. T. (2010). Real lesson in virtual worlds: using virtual worlds to educate
and train business students. In C. Wankel, M. Marovich, & J. Stanaityte (Eds.),
Cutting-edge social media approaches to business education: Teaching with LinkedIn, Facebook, Twitter, second life, and blogs. Charlotte, North Carolina: Information Age Pub Inc.
Wood, N. T., Allen, D., & Sullivan, M. R. (2008). Welcome to the matrix: E-learning
gets a second life. Marketing Education Review, 18, 48e53.
Wooldridge, B. R. (2006). The power of perception: an active/experiential learning
exercise for principles of marketing. Marketing Education Review, 16(2), 5.
Yamarik, S. (2007). Does cooperative learning improve student learning outcomes?
The Journal of Economic Education, 38(3), 259e277.
Yi, M. Y., & Davis, F. D. (2003). Developing and validating an observational learning
model of computer software training and skill acquisition. Information Systems
Research, 14(2), 146e169.
Gwen Noteborn MSc. MA obtained her MSc in Strategic Marketing and MA in Conflict
Management and works as a Researcher at the Department of Educational Research and
Development at Maastricht University, she also leads a small team of educationalist at
the Edl@b (educational lab) of Maastricht University. Within Edl@b companies, students
and educational researchers work together to conduct and implement educational experiments in a classroom setting using new media technologies. Within her job she led
several successful projects redesigning traditional curricula by implementing new/multi
media tools. Her research focuses on the effectiveness of social media tools in education.
Noteborn has been teaching the course Brand Management for three consecutive years
and is responsible for the implementation of Second Life within the course Brand
Management. For her work in the Brand Management course she received the
234
educational Prize for an outstanding contribution to education. Noteborn has been
published on topics related to learning in virtual worlds and their effectiveness.
Prof. Dr. Amber Dailey-Hebert is a Full professor at Park University, USA. She received
her Ph.D. in Education from Cornell University, investigating how instructor practice
informs student learning outcomes. She has also served as an online course developer,
instructor, and mentor for online course facilitation and instruction, is the Associate
Editor of InSight: A Journal of Scholarly Teaching, and chairs the Research Committee for
the Association of Continuing and Higher Education. Dailey-Hebert has been published
on topics related to leading organizational change, faculty evaluation models online, and
faculty professionalization, and is currently conducting research in integrative eLearning
andragogies and higher education. She has served as the Associate Dean of the School for
Online Learning, Adult Education Department Chair and Program Coordinator, and as the
Founding Director of the Center for Excellence in Teaching and Learning.
Katerina Bohle Carbonell MSc. Obtained her MSc in Management of Learning at
Maastricht University and is a researcher at the Educational Research and
Development at Maastricht University. Katerina developed her passion for online
learning when writing her Master Thesis in this field and is now a PhD candidate at the
Education Department of the Faculty of Health, Medicine and Life Sciences at Maastricht University.
Prof. Dr. Wim Gijselaers is a professor in the field of professional learning and head of
the department of Educational Research and Development (ERD), Maastricht University, the Netherlands. His research addresses effects of social and cognitive processes
on professional development. Next, he researches how student learning can be
improved through course and program innovation. His current research projects deal
with how visualization tools can guide engineering teams in new product development, how talented people can become experts in a professional domain, and how
drop-out in professional education can be reduced through curriculum interventions.
He is chief-editor of the Springer book series “Innovation and Change in Professional
Education” and associated editor of the Springer book series “Advances in Business Education and Technology”. His work has been published in many international refereed
journals and edited volumes.

Essential knowledge for academic performance: Educating in the

Transcription

Similar documents

Educational Games - Games that Teach, not Preach

Paper - Ersin Yumer

PDF (Author`s version) - OATAO (Open Archive Toulouse Archive

Retina, Cornea and Other Eye Procedures

Bunion Procedures with Surgery of the Lesser Toes

Procedural Justice for Law Enforcement: An Overview

quality of life

Brickell Ten Condos Brochure

Toward Generating 3D Games with the Help of Commonsense

Revised Pre-Screen Application

Alison Brettle - CILIP Conference