USEFUL E-LEARNING PROCESS DESCRIPTIONS

Steffen Mencke, Fritz Zbrog and Reiner Dumke

Faculty of Computer Science, Otto-von-Guericke University, Universitätsplatz 2, Magdeburg, Germany

Keywords:

E-learning, process.

Abstract:

E-learning is nowadays one of the most interesting of the “e-”domains available through the Internet. Deﬁning

e-learning as a single process, just with content development and content delivery/maintenance, only depicts

a limited view to its complex nature. Many more detailed processes exist and can be described, analysed and

optimised.

This paper addresses this aspect. It is intended to provide background information about e-learning processes

and their possible descriptions. They are used to start a discussion about useful and applicable e-learning

process descriptions.

1 INTRODUCTION

E-learning is nowadays one of the most interesting

of the “e-”domains available through the Internet.

In general it refers to a wide range of applications

and processes designed to deliver instruction through

computational means (Juneidi and Vouros, 2005).

A process is formally deﬁned as a set of activi-

ties associated with a set of events, where an event

is an internal or external signal, message, variable,

scheduling, conditional change, or timing that is spec-

iﬁed in association with speciﬁc activities in a process

(Wang and King, 2000).

An e-learning process thereby is a special process,

whose domain is e-learning and the process transi-

tions involve e-learning-related activities to change

certain states within this domain.

A reasonable discussion must base on a solid fun-

dament of knowledge about the targeted problem. Af-

ter this introduction section 2 provides those needed

information about e-learning processes and possible

process descriptions. Section 3 discusses the appli-

cability of process descriptions for certain identiﬁed

e-learning processes. In section 4 we ﬁnish with a

conclusion and some remarks about future work.

2 E-LEARNING DESCRIPTIONS

2.1 E-learning Process Dimensions

E-learning itself is a process containing two major

phases: content development (additionally including

planning, design and evaluation) and content delivery

(additionally including maintenance). Its nature is it-

erative (cp. ﬁgure 1). Evaluation is recommended for

continuous improvement (Giotopoulos et al., 2005).

Content Development Process

Learning

Environment

Delivery &

Main-

tenance

Design

Planning

Evaluation

Production

Figure 1: Iterative process of E-learning (cp. (Giotopoulos

et al., 2005)).

The stages of a general e-learning process are

planning, design, production, evaluation, delivery and

maintenance, instruction stage and marketing (Khan,

2004).

There exist more specialised e-learning processes

being categorised in the following according to their

domain of application. The proposed dimensions and

some exempliﬁed e-learning processes are:

◦ Technological dimension

– E-learning platform operation

– Technical-enhanced dissemination process

◦ Organisational dimension

– E-learning establishment and process

– Course and organisation administration

460

Mencke S., Zbrog F. and Dumke R. (2008).

USEFUL E-LEARNING PROCESS DESCRIPTIONS.

In Proceedings of the Fourth International Conference on Web Information Systems and Technologies, pages 460-463

DOI: 10.5220/0001527004600463

 SciTePress

– Evaluation through the entire lifecycle

– Coordination process

– E-learning innovation process

◦ Authoring dimension (refers to the classic content

creation stage)

– Learning object and course design

– Didactical design

◦ Learning and teaching dimension (refers to the

classic content delivery stage)

– Presentation process

– Learning process

2.2 Process Descriptions

Processes in general can be described using various

approaches. The identiﬁed classes of process descrip-

tions reveal an increasing degree of formalisation –

informal process descriptions, graphical process de-

scriptions and formal process descriptions.

Some process description approaches were al-

ready used in the previous subsection about e-learning

processes, like e.g. textual descriptions. Other re-

sources refer to activity lists, hierarchies (Pentland

et al., 1999) or tables as informal approaches to de-

pict processes with their states and activities.

More graphical approachesto model stepwise pro-

cesses are diagrams and graphs as for example the one

in ﬁgure 1 about the general e-learning process.

A last class of approaches categorises formal de-

scriptions like algebraic possiblities, languages or

rules. Other examples base on petri nets, like the

event-driven process chain (Müller et al., 2005) or

ontologies, e.g. describing the structure of didacti-

cal ontologies which can be used to model didactical

process expertise (Mencke and Dumke, 2007).

3 PROCESS DESCRIPTIONS FOR

E-LEARNING PROCESSES

As already introduced processes are determined by

sequence of states. This sequence can be inﬂuenced

on certain levels and depicts the nature of a process’

activities - in other words it reveals a system be-

haviour. The states of the process base on certain do-

main objects. Within e-learning that can be a learning

object, a course, an e-learning system, etc.

These dimensions - the nature of state domain ob-

jects and the activities nature - are used to categorize

already identiﬁed e-learning process classes.

According to the classiﬁcation in table 1 the rigid

nature of activities as well as of state domain objects

are used in closed processes. The activities and do-

Table 1: Classiﬁcation of e-learning processes according to

the processes’ nature.

ACTIVITIES’

NATURE

STATE DOMAIN OBJECT’S

NATURE

rigid ﬂexible

rigid

technological,

organisational

probabilistic

authoring,

learning

situative

learning

main objects rarely change. Technological and organ-

isational processes are categorised here. More open

processes deal with ﬂexible objects and ﬂexible ac-

tivities. Within e-learning open processes are author-

ing and learning processes. Depending on the type of

learning, learning processes can be completely open

and therefore guided, but not speciﬁcly bounded to

any predeﬁned learning path space.

3.1 Closed e-Learning Processes

Main evaluation criteria for closed e-learning pro-

cesses are stability, safety, being optimised and that

they meet time constraints. Routine must be achieved.

This process type is already well known and re-

searched. There exist multiple proven approaches

to meet the several levels of routine in different do-

mains. Roadmaps deﬁned based on maturity models

ﬁt the requirements of process management, follow-

ing existing standards, measuring and measurement-

based adaptation to understandand, model and im-

prove closed processes. An existing maturity model

for e-learning is eMM (Marshall, 2007). Its levels are:

5. Optimising: continual improvement

4. Managed: ensuring the quality of e-learning re-

sources and student outcomes

3. Deﬁned: deﬁned process for development

2. Planned: clear objectives for e-learning

1. Initial: ad-hoc processes

Roadmaps of maturity models use the informal

textual approach to deﬁne rules to help an institution

to further develop their closed e-learning processes.

Graphical approaches are only used for the human

reader for a better understanding. Executable formal

approaches are not useful because closed e-learning

processes are too complex and rarely can be auto-

mated evaluated due to the subjective nature of their

analysis.

USEFUL E-LEARNING PROCESS DESCRIPTIONS

461

3.2 Semi-Open e-Learning Processes

Semi-open processes cannot be evaluated simply by

the routine of its execution. Authoring and learning

based on strict course structures reveal a rigid or

maximal probabilistic activity nature. There are

predeﬁned degrees of freedom to choose different

activities and to change the objects the states are

based on. These objects, e.g. learning objects or

learning steps, are ﬂexible in the manner that they can

and must be adapted to reﬂect the changes within the

environment: new knowledge needs to be integrated

and new teaching/learning approaches to be applied.

Factors to be taken into consideration are e.g.:

◦ Relative completeness, e.g. in terms of exten-

sion, issue representation, maintenance conformity,

avoidance of semantical thinning and individualisa-

tion (concept overvaluation)

◦ Didactical preparation, e.g. in terms of compre-

hensibility, goal conformity, logical consistency

For semi-open e-learning processes also exist ap-

plicable process descriptions. That refers e.g. to the

PELO model for authoring (Müller et al., 2005). The

main steps are process modeling, process execution

and process measurement. For the ﬁrst step, the au-

thors use a formal visualisation technique, the Event-

driven Process Chain that is based on Petri-net theory.

For the learning process guidance certain models

exist (e.g. SCORM (Advanced Distributed Learning

(ADL), 2006)). They are not completely sufﬁcient

due to several reason. So they still lack from an appro-

priate deﬁnition of difﬁculty and a sufﬁcient deﬁnition

of usage rights and educational activities (because of

the often used IEEE LOM (IEEE LTSC, 2003)). Fur-

thermore there is a subjective selection of educational

material types or missing detailled speciﬁcations for

some types of media (Simon, 2002).

3.3 Open e-Learning Processes

Open e-learning processes are the most complex ones.

There are high degrees of freedom for activities as

well as for the state’s objects. The nature of the ob-

jects as well as their types can extremely vary. For

a learning process there are for example different

culture-related, individual disposition-related, intrin-

sic and extrinsic motivation or timely emotional in-

ﬂuences. Other variables are the learning situation,

the individual learning type and the learning content.

The main goals for open e-learning processes

speciﬁcely directed to learning next to individual

knowledge increase are not to classify but to individu-

ally treat learners, to keep the learning motivation and

to provide learning possibilities that can adapt to in-

dividuals and their speciﬁc situation. The learner is a

partner within the process, not a target.

Some criteria for evaluation of process outcomes

are:

◦ Content quality according to the learning goal:

– Degree of the content’s abstraction

– Difﬁculty level of content

◦ Flexibility of the learning system according to in-

dividual learning and life situations

– Method conformity

◦ Individual learning goal adaptations by the learner

– Individual knowledge gain

– Degree of content understanding, repitition and

applicability

– Achieving the didactical goal

Again routine criteria and related process descrip-

tions are not sufﬁcient. So far no single system pro-

vides sufﬁcient process support that comprises all di-

mensions. Ontologies can be an approach to take into

account occuring diversity (Simon, 2002), (Mencke

and Dumke, 2007).

3.4 Ontology-based e-Learning Process

Description

As argued above, most process descriptions are not

sufﬁcient to model the complex inﬂuences that may

occur within open e-learning processes. A ﬂexible

and semantically deﬁned approach is needed to guar-

antee applicability, reusability and extensibility.

Therefore the authors propose an extension of

the ontology for e-learning processes described in

(Mencke and Dumke, 2007). Other basic character-

istics are described in (Lin and Strasunskas, 2005).

This ontology’s tasks are twofold: providing a gen-

eral scheme for process description as well as serving

as a starting point for process optimisation.

In the proposed ontology a process is modelled as

a graph of LearningActivities, each ﬁnalised with a

LearningState. Conditions are used to deﬁne transi-

tions between LearningStates and LearningActivities.

Each LearningState can be further semantically

described by the deﬁnition of Dimensions. This

feature is supposed to be further adapted and ex-

tended to depict suitable descriptions for each pos-

sible implementation. A LearningState is the set of

LearningStates of each sub-LearningActivity of the

LearningStateï£¡s LearningActivity. Here appropri-

ate mechanisms still need to be developed to (a) inter-

pret subset of LearningStates to identify the next ap-

WEBIST 2008 - International Conference on Web Information Systems and Technologies

462

propriate LearningActivity and (b) to analyse the user

to identify suitable dimension concepts for interpreta-

tion. But this is not the focus of this paper.

These feature are the base of the ontology’s capa-

bility for storing complex e-learning processes. Fig-

ure 2 shows the developed ontology.

LearningActivity LearningState

Condition

Dimension

ConditionOperator Variable

hasAnOperator

hasLeftSideValue

hasRightSideValue

hasDimension

hasSubLearningState

hasSubLearningActivity

learningActivityLeadsTo

defaultNext-

LearningActivity

learningStateLeadsTo

hasLeftSideValue

hasRightSideValue

hasAsNextCondition

conditionLeadsTo

Figure 2: Ontology for e-learning process description.

4 CONCLUSIONS AND FUTURE

WORK

In this paper the authors analysed different e-learning

process descriptions and possible process descrip-

tions. Their classiﬁcation is used to start a discussion

about the applicability of process descriptions for cer-

tain e-learning processes. Three main classes of them

are identiﬁed and appropriate description approaches

are suggested.

Futhermore, for open e-learning processes as the

most complex class, an ontology-based description is

proposed by the authors.

In the future existing user models need to be ana-

lysed for their capability to work with the ﬂexibility

of the proposed ontology. Another aspect is the de-

scription of the interpretation mechanism that uses the

existing ontologies and user models to ensure the ﬂex-

ibility of the learning process support.

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