e-Learning and e-Assessment in Tourism and Hospitality

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Internet advances enable students to receive and interact with educational materials and to
engage with teachers and peers in ways that previously may have been impossible. Indeed,
because of its three unique features namely, interactivity, connectivity and technological
convergence, the Internet has irrevocably altered how people access information and how
much information anyone can access, while local and wide-area networks release the
Internet as a learning resource with software tools that enable interactive communication.
e-Learning or Internet-based learning, therefore, offers significant opportunities for those
in the tourism sector to up-grade skills and knowledge, as its flexibility matches the specific
conditions of work within the sector (Sigala, 2002). Moreover, good e-learning can
foster collaborative learning by drawing on the expertise of leading subject authorities in
all key subject areas, which in turn also allows students to experience multicultural diversity
and teamwork by interacting online with people of different social and cultural background.
The acquisition of social, multicultural and communication skills are of a crucial
importance for tourism graduates (Christou, 1999), because the inherently multinational
and cultural tourism workplace requires a knowledgeable workforce that can work collaboratively
irrespective of their spatial, time and cultural differences. e-Learning also acclimatizes
graduates to the changes occurring in the tourism workplace, e.g. growth of
e-business applications and increasing alliances and merges among tourism companies.
However, although e-learning is widely being adopted for enhancing and complementing
tourism and hospitality instruction (Sigala & Christou, 2003) and its advantages for tourism
and hospitality education are extensively argued (Sigala, 2002; Cho, Schmelzer, &
McMahon, 2002; Clements, Buergermeister, Holland, & Monteiro, 2001; Christou & Sigala,
2000), little is still known on how to design and implement effective e-learning platforms.
Moreover, although an increasing number of tourism and hospitality educators are adopting
and incorporating Internet tools in their instruction, only very few of them are fully exploiting
the Internet’s capabilities to transform and extend their pedagogical models (Sigala &
Christou, 2002). On the other hand, it is generally agreed that the reimplementation of
conventional models borrowed from classroom based or distance education that are focused
on passive transmission would permit only marginal improvements. Thus, there is a need to:
examine how knowledge is acquired and how online learning occurs and so, illustrate how
e-learning pedagogy should be designed; investigate the e-assessment pedagogies that can
support and foster the former; and identify the factors influencing the effectiveness of elearning
experiences. This thread aims to achieve these objectives by reviewing the literature
and current practices as well as by providing insights from research studies and best
practices. Finally, future trends and developments are also discussed.

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The internet’s capabilities imply a different type of thinking in terms of how to make full
use of its learning-enhancing features and pedagogical potential. In particular, the internet’s
affordance for enhanced communication provides great opportunities for combining
collaborative techniques with technology to dramatically enhance the learning process and
learning outcomes (Sigala, 2002; Cho et al., 2002). Harasim (2000) also advocated that the
asynchronous, hypertext and multimedia-based nature of the technology represents cognitive
advantages —— such as flexibility with regard to the nature of interaction, reflection on
stored communication or reduction of discriminatory communication patterns based on
physical features and social clues —— that provide an augmented domain for collaborative
learning. The electronic implementation of collaborative learning often results in the
development of a virtual classroom, whereby tools such as electronic bulletin boards, mail,
grade books, quizzes and lectures are used to provide feedback, distribute material and
develop a learning community similar to a traditional classroom. The general effectiveness
of collaborative learning in traditional classrooms is supported by decades of research
(e.g. McKeackie, 1980; Palloff & Pratt, 1999), while recent studies (McConnel, 1994;
McConnel, Hardy, & Hodgson, 1996; Campos, Laferriere, & Harasim, 2001) point to
Online Collaborative Learning (OCL) as an effective learning method within electronic
environments. Thus, e-learning platforms are increasingly adapting a pedagogical
approach of OCL that is based on the theoretical underpinnings of constructivism (critical
thinking skills) and collaboratism (detailed literature review in Sigala, 2002, 2004b).
Briefly, constructivism argues that knowledge is created by searching for complexity
and ambiguity, looking for and making connections among aspects of a situation and speculation.
So, when learners are exposed to new information, each learner evaluates and
analyses it, sees the relationships between the new information and his/her existing knowledge
and makes inferences and judgments for new knowledge (Kafai & Resnick, 1996). In
other words, to enhance learning, students should think critically, have the ability of
analysing situations, search for evidence and seek links between a particular situation and
their prior knowledge and experience (Sigala, 2002). In such learning environments,
instructors should act as facilitators, while students should actively participate in the learning
process and control their learning pace.
Collaborative learning evolved from the work of psychologists (e.g. Johnson & Johnson,
1975) and involves social (interpersonal) processes by which a small group of students work
together to complete a task designed to promote learning. Thus, collaborative learning
involves the creation and interpretation of communications among persons/groups that might
have different understandings and opinions (Sigala, 2002), which in turn enhance learning by
allowing individuals to exercise, verify, solidify, and improve their mental models.
Dillenbourg and Schneider (1995) identified three collaborative learning mechanisms
directly affecting cognitive processes. First, conflict/disagreement, because it forces learners
to seek information and find a solution. Moreover, internalization of interactions with more
knowledgeable peers, explanations from more advanced peers as well as self-explanations
(self-explanation effect) can also enhance learners’ learning processes. In collaborative learning,
group processes are a part of the individual learning activity ——individual and collective
activities are mutually dependent on each other. This is because the learner actively constructs
knowledge by formulating ideas into words, and these ideas are built upon through
reactions and responses of peers. In other words, individual learning is a result of group
processes and so, learning is not only active but also interactive. Thus, collaborativism may
also be seen as a variation of constructivism that stresses the cooperative efforts among students
and instructors in the learning process (Sigala, 2002).

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Sigala (2002) identified and analysed in detail the different e-learning models and their
developmental stages. In her model she identified three major stages of e-learning environments
that educators can implement. The transfer of traditional instruction on the
Internet is the earliest and most extensive category of online instruction. e-Learning models
under this category do not fully exploit Internet capabilities for transforming and
enhancing instruction, but they rather imply and demonstrate a simple transfer of traditional
practices on the Internet, e.g. information distribution and publishing. According to
Sigala and Christou’s (2002) findings, this simple webification of learning processes is
evident in the electronic distribution of learning material (e.g. lecturers’ websites with
lectures’ notes, presentations, learning material, references, etc.), in electronic
student-to-tutor and student-to-student interactions (synchronous and/or asynchronous
electronic communications overcome place and times boundaries and are of great support
to students conducting their industrial placements in international settings) as well as in
electronic assessment procedures. Analytically, Internet tools are used for communicating
with students, simulating discussions found in traditional classrooms and extending
them beyond the classroom walls, e.g. McDonnell (2000) described how they used
Internet and computer simulations for simulating classroom discussions. However, while
the technology tends to support a certain degree of egalitarian participation, and does
allow users the freedom to input messages at their convenience, the conditions which are
needed to produce good educational discussions are far more complex, more peopledependent
and more educationally determined than mere technology will ever influence
very significantly. Sigala (2004a) reported that students’ negative perceptions towards the
internet’s features and their learning style significantly inhibited them in participating in
online forums. As concerns assessment, the Internet and web-in-a-box software is used
for disseminating traditional evaluation practices, e.g. multiple choice tests, without
changing or even enhancing their form and content. Mason (1998) advocated that existing
assessment practices are ill suited to the digital age in which using information is more
important than remembering it, and where reusing and applying material should be
viewed as a skill to be encouraged, not as a plagiarism to be despised. Overall, as in this
e-learning model the principles and aims of instruction do not change, the roles and tasks
that students and tutors should assume and undertake also remain the same.
Consequently, such practices result in computer-based learning environments that can be
characterized as “page turning devices” of learning material that is a simple digital photocopy
of current texts and so, which fall short of the interactive, user-centred features
originally made for them.
The second wave of e-learning pedagogy models, online collaborative and constructive
learning models, illustrates a more educational than technology determined approach to
e-learning. The internet capabilities imply a different type of thinking in terms of how to
make full use of its learning-enhancing features and pedagogical potential. Because one of
the key affordances of the Internet is for communication (e.g. through email, bulletin
boards, chats, electronic conferencing), the combination of collaborative and constructivist
(or critical thinking) techniques with technology are argued to significantly enhance the
learning process and learning outcomes dramatically. The electronic implementation of
collaborative learning often results in the development of a virtual classroom, whereby
tools such as electronic bulletin boards, chat rooms, e-mails, grade books and quizzes are
used in order to provide feedback, distribute material and develop a learning community
similar to a traditional classroom (Hammond, 2000; Wachter, Gupta, & Quaddus, 2000;
McConnell et al., 1996; Cho and Schmelzer, 2000). Constructivism is an epistemology of
how people learn and assimilate new knowledge asserting that knowledge is acquired by a
process of mental construction. Both Harasim (2000) and Akyalcin (1997) (see literature
review in Sigala, 2002) analysed and illustrated with several examples, how internet tools
can support the four following processes of knowledge construction as initially presented
by Piaget (1977):

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1. Assimilation: associate new events with prior knowledge and conceptions;
2. Accommodation: change existing structures to new information;
3. Equilibrium: balance internal understanding with external “reality” (e.g. other’s understanding);
4. Disequilibrium: experience of a new invent without achieving a state of equilibrium.
Koschmann, Meyers, Feltovich, and Barrows (1996) also considered discourse and interactions
as a fundamental aspect of learning by arguing that “learning is enhanced by
articulation, abstraction and commitment on the part of the learner: instruction should
provide opportunities for learners to articulate their newly acquired knowledge”.
Articulation is a cognitive act in which the student presents, defends, develops and
refines ideas. Thus, in order to articulate their ideas, students must organize their
thoughts and information into knowledge structures. Ultimately, active learners’ participation
in online discourses leads to multiple perspectives on issues, a divergence of ideas
and positions that students must sort through to find meaning and convergence. However,
it is the conflict and collision of adverse opinions that lead to cognitive growth and development
of problem-solving skills. Thus, in collaborative learning settings, online discourses
are the “heart and the soul” of online education enabling interaction, conceptual
exchange and collaborative convergence across differences of knowledge, skills and attitudes.
Indeed, collaborative learning should thrive on these differences. Overall, computer
conferencing and network capabilities of the internet tools enable communication
and discourses that are best described as a form of discourse-in-writing. The unique
attributes of communication in e-learning environments and the cognitive activities that
they enhance for augmenting the online learning experience are summarized by Harasim
(2000) as follows:
● Many-to-many (group communication) enables: motivational (socio-affective) benefits
of working through problems with peers; active exchange: rich information environment;
identification of new perspectives, multiplicity; opportunity to compare, discuss,
modify and/or replace concepts (conceptual exchange); encouragement to work through
differences and arrive at intellectual convergence;
● Time independence supports: 24 h access, users can respond immediately or reflect and
compose a response at their convenience; ongoing, continuous knowledge building; participation
by users at their best learning readiness time;
● Place independence allows: access to the wealth of Web resources (as well as peers and
experts); shared interests, not just shared locations among participants;
● Text-based/media-enriched messaging encourages and contributes to: verbalization and
articulation of ideas; focus on message rather than on the messenger (reduced sociophysical
discrimination); clear expression of ideas; rich database/web of ideas;
● Computer-mediated environments enable: searchable, transmissible and modifiable
archived database; multiple passes through conference (discourse) transcript; building
tools to exchange and organize ideas and support collaborative learning; building templates,
scaffolds and educational supports.

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Salmon (2002) provides several examples and cases on how to develop collaborativeconstructivism
e-learning platforms and activities, while in the context of tourism and hospitality
education examples and suggestions are given in Sigala (2004a, b) and Cho and
Schmelzer (2000). Constructivism online communications are also helpful and valuable to
researchers conducting doctoral and research studies, as online discussions and communications
can be used for several purposes such as idea generation, concepts debates,
material identification and exchange, collaborative research projects etc. Nowadays, a similar
and widely known and used application is the communications and interactions found
in tourism e-mail lists and servers. Overall, the specific nature and features of tourism education
and industry (such as multi- and inter disciplinary, international, dynamic and
changing, multicultural, people-centred) enhance the applicability, appropriateness and
value of constructive communications in tourism e-learning environments. For instance,
the integration of online communications and debates can be designed in order to foster
and include in discussions opinions from different disciplines, from the professional circles
and from the international community in an ad hoc basis, i.e. when it is required. This
creates as Cho and Schmelzer (2000) called it “just in time” tourism education environments
allowing learning to be continuously updated and developed according to industry
needs and changes.
Nowadays, researchers and designers are seeking more sophisticated learning theories
based on proven research showing how brains works, e.g. recent neuroscience research
reveals how the brain’s emotional system influence and how individuals learn and memorize
facts. Such developments reflect research (e.g. Martinez, 1999; Martinez & Bunderson,
2000) based on a learning orientation approach, which attempts to reveal the dominant
power of emotions and intentions on guiding and managing cognitive processes (no longer
demoted to a secondary role). Moreover, by understanding the structure and nature of the
complex relationships between learning orientations and interactions, the learning orientation
research aims at developing instructions that do not fit the average person but fit groups
of students with particular aptitude patterns. Here, Sigala (2002) predicted the development
of personalized and adaptive (mass customization) e-learning models that would be customized
to individual learners based on an individual’s emotions, intentions and intentions’
about why, when and how to use learning and how it can accomplish personal goals. These
models are very useful because effective e-learning instruction should provide multiple
ways to provide instruction and e-learning environments so that all learners will want to
learn on the Web and continue to have opportunities for success. In this way, the benefits of
personalized e-learning to individual differences would be the ability to address important
human issues previously managed by instructors in the classroom (e.g. lack of confidence,
impatience, mistakes, boredom).
Overall, Table 1 provides some examples of how e-learning models can and could be
applied in tourism education.

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3-13-2009 22:59

Table 1: Examples of e-learning models in tourism education.

[ by Tourism at 3-13-2009 22:59 edited ]

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Webster and Hackley (1997) remarked that although students’ performance represents a
key aspect of teaching effectiveness, they highlighted that the following dimensions also
capture the concept of effectiveness: student participation and involvement; cognitive
engagement; technology self-efficacy (i.e. ones belief on his capacity to interact with a
given technology); perceived usefulness of the technology; and the relative
advantages/disadvantages of online delivery. Bernard, Rubalcava, and Pierre (2000) also
argued that e-learning should be evaluated on its three dimensions namely commitment,
coordination and communication by measuring variables such as group cohesion and productivity,
use of resources and level of communication. Moreover, because e-learning
requires learners to be active participants of their own learning, other learner’s variables
should also be considered. However, previous studies investigating the learning
quality/effectiveness have generally used students’ grades, attitude surveys and observational
data (Porras-Hernadez, 2000). Other studies revealed the impact of affective aspects
such as confidence in learning abilities and expectations (Brosnan, 1998; Schlechter,
1990). More recent studies evaluating e-learning are also focusing on specific abilities and
attitudes needed in e-learning by including student’s perceptions of themselves (Bernard
et al., 2000; Martinez, 1999) rather than only looking at students’ perceptions of technology,
tasks and their ability with technology. Porras-Hernadez (2000) also stressed the need
to include learners’ capability for educational achievement in general, while Hammond’s
(2000) findings revealed that two learners’ factors determine learning effectiveness namely
cognitive aspects (e.g. previous experience in mediated education and computer skills) and
affective variables (e.g. expectations, self-efficacy for self-regulated learning, perceptions
of instructors and their efforts, feelings of anxiety and success). Overall, students’ factors
determining e-learning effectiveness include: prior experience with technology; country of
origin and native tongue; educational skills and self-discipline; perceptions of the self and
self-regulatory processes. The latter can crucially determine students’ participation and elearning
effectiveness, since e-learning emphasizes and requires learners’ ability and
responsibility of their own learning. Sigala (2004a) also found that students’ perceptions
on the electronic medium significantly affected their participation in OCL. Online discussions
have four major characteristics: messages are permanent; messages are public; communication
is asynchronous; and messages can be edited before sending. Depending on
the way students perceive these attributes, students’ participation on online forums varies
considerably. For example, the permanency of messages may encourage learners to contribute
as they can easily access and refer to past debates. However, this can also discourage
communication as threads show that their texts are open for scrutiny and that they
cannot easily retract anything they would write.
The following technology issues were also found to affect e-learning effectiveness
(Dillon & Gunawardena, 1995; Laurel, 1990; Blattner & Dannenberg, 1992; Martinez,
1999): (a) the medium’s reliability, quality and richness; (b) capability for both synchronous
and asynchronous communication; (c) quality of interface, e.g. factors regarding:
ease of use, navigation, screen design, information presentation, aesthetics and overall
functionality; (d) the perceived richness (synchronous, asynchronous and multimedia communication
tools) of the used technology.

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However, it is not the technology but rather its instructional implementation that determines
learning effectiveness. Thus, the role of the instructor becomes central and instrumental
in the effectiveness of e-learning. Actually, the following instructor factors can
influence learning outcomes (Salmon, 2002): attitude towards technology, control of technology
and teaching style, e.g. the way he/she facilitates/mediates e-learning platforms. In
particular, the instructors’ facilitating and mediating capabilities and roles are crucially
important because unless these are effectively achieved, serious problems may arise. For
example, an online conference may turn into a monologue of lecture type material to
which very few responses are made or to a disorganized mountain of information that is
confusing and overwhelming for the participants. To avoid such situations, Harasim (2000)
stressed that instructors should adapt an online instruction teaching paradigm that is away
from the traditional lecture format as well as become active e-moderators. Actually,
instructors must assume three crucial tasks namely contextualizing, monitoring and
meta-communication functions (Sigala, 2004b), which Salmon (2002) summarized into
the concept of weaving. The first two functions aim to compensate for the absence of physical
cues found in traditional classrooms, while meta functions aim to resolve problems in
communication that are addressed in classrooms by body language and to summarize the
state of a discussion to provide the sense of accomplishment and direction.
In investigating the factors affecting e-learning effectiveness in hospitality, Sigala
(2004a) identified three major factors while also discussing several ways in addressing
them: (a) instructor factors: instructor attitudes towards learners; instructor technical competence;
and instructor efforts for facilitating/mediating forums and interactions; (b) technology
factors: easy access and navigation; interface; and interaction both with peers and
instructors; and (c) student factors: students’ ability of controlling learning processes; students’
effort in searching and understanding learning material; and students’ ability to participate
in collaborative processes. Sigala’s (2003) findings also revealed that students’
cultural background and gender can crucially affect their level and type of contribution in
e-learning activities and communities. However, Sigala (2004a) concluded that future
research should aim to assess e-learning effectiveness also in terms of the communication,
social, interpersonal and technology skills that it aims to enhance.

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e-Learning activities and processes are not complete and may not lead to the desirable
learning outcomes, unless they are integrated and aligned with appropriate assessment
strategies. This is because it is common that assessment related tasks attract students’
attention at the expense of non-assessed tasks. Thus, assessment criteria and processes can
significantly direct, motivate and guide students’ learning processes. In this light, interest
in the evaluation of e-learning and online discussion forums is continuously increasing and
demonstrated in the great number of tools applied for teasing out key aspects of the interaction
that can lead to improvements in online learning environments (Pittman, Gosper, &
Rich, 1999). However, the appropriateness and impact of such tools on reliably assessing
e-learning processes and outcomes as well as on fostering and supporting skills’ development
are not always effective neither do they support student-centred learning. In general,
e-assessment methods are classified into two categories namely quantitative and qualitative
assessment tools.
Quantitative methods aiming at assessing the amount, frequency and direction/interaction
of online discussions have pushed instructors to calculate statistics such as number of
online users, frequency of access, number of messages per student, number of
threads/messages per thread (Harasim, 1989) or to develop “message maps” for reflecting
the flow of communication within the group (Levin, Kim, & Riel, 1990). Although such
metrics are good at identifying the level of students’ adoption and engagement in
e-learning processes, there is a danger of implying that the level of online participation
reflects the level of learning. Moreover, such assessment metrics are limited in their ability
to assess and motivate students towards skills’ development, simply because they
ignore messages’ content. Instead, assessing students solely based on their level of online
participation may lead to: information/messages overload that have nothing to do with the
learning task; limited student guidance and direction as to what and how has to be
achieved; increased students’ stress for catching up and reading messages that in turn
leaves limited time for reading, reflection, concepts’ internalization and assessment.
Qualitative assessment methods aim to address the limitations of previous metrics by
exploiting the transparency of online discussions (i.e. the fact that all communication is easily
organized, stored and retrieved) and analysing text-based archives/transcripts for understanding
and evaluating e-learning processes. This is achieved by first breaking the transcript
down into small units and then classifying these units according to the content. Different
approaches have been developed and applied for identifying units’ categories. Categories
may be defined either retrospectively in order to capture the flavour of a particular forum
(e.g. McLoughlin, 2002; Mowrer, 1996) or a priori based on the learning processes and tasks
in which theory implies that students should be engaged for enhancing their learning.
However, it is the second level of analysis that is needed to evaluate e-learning and guide the
use of online discussion environments. This is because of two major reasons. First, students
are assessed based on evidence of the learning processes that they have been engaged.
Secondly, by making students aware of the assessment criteria (i.e. the predefined units’ categories)
in advance, instructors can get students acquainted to the learning processes while
also directing and motivating their efforts towards the tasks they need to engage.

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For developing unit categories, a number of theoretical models of e-learning processes
exist in the literature (see literature review in Sigala, 2004b), but the most effective is argued
to be that developed by Gunawardena, Lowe, and Anderson (1997) as it reflects the “gestalt”
of the entire online discussion rather than focusing on links between specific messages. A
gestaltist approach to analysing the interaction of the entire online conference was central to
Gunawardena et al.’s (1997) purpose to evaluate evidence for the social construction of
knowledge. Their own preferred method of content analysis was developed to capture the
whole progression of ideas as they were reflected at following different phases of the debate:
● Sharing/comparing information: this phase may include an observation, opinion, agreement,
corroborating example, clarification and/or identification of a problem;
● Discovery and exploration of dissonance or inconsistency among the ideas/concepts or
statements advanced by other participants: this is defined as an inconsistency between a
new observation and the learners’ existing knowledge and thinking skills, e.g. identification
of differences of terms/concepts/schema and questions to clarify the extent of disagreement;
● Negotiating meaning and co-construction of knowledge: e.g. negotiation/clarification of
the meaning of terms, detection of areas of agreement, proposal of a compromise/
co-construction;
● Testing and modification of proposed synthesis: testing against an existing cognitive
schema, personal experience, formal data experimentation, contradictory data from the
literature;
● Agreement, statements and application of newly constructed meaning: including summarizing
agreements/metacognitive statements showing new knowledge construction
and application.
Overall, it becomes evident that assessment of online collaborative learning should not
focus solely on metrics reflecting the quantity of students’ interaction but also on assessment
criteria that simultaneously consider the quality and learning ability of students’
interactions/communications. Assessing students based on both the quantity but also the
quality of their interactions should direct and motivate them towards the online and constructivism
creation of knowledge and skills. Sigala (2004b) described how Gunawardena
et al.’s (1997) constructivist model of online assessment has been applied for designing
collaborative e-assessment strategies and integrating/aligning them with e-learning strategies
that can overall motivate and foster the development of constructivism students’ learning
processes and outcomes. Moreover, some additional insights and lessons learned from
this case study are presented below.