LEARNER-ORIENTED APPROACH FOR ENTERPRISE

SYSTEMS IN HIGHER EDUCATION

USING TEL-BASED CONCEPTS

Research Positioning Paper

Dirk Peters, Liane Haak and Jorge Marx Gómez

Faculty II, Department of Computing Science, Carl von Ossietzky University of Oldenburg

Ammerländer Heerstr. 114-118, 26129 Oldenburg, Germany

Keywords: Learner orientation, Enterprise systems, Application usage mining, Higher education, Technology enhanced

learning, Adaptive learning environment.

Abstract: Higher education institutes like universities or universities of applied science can not ignore the need to

teach well know application and information systems, like Enterprise Systems, e.g. ERP-Systems. Case

studies are the most chosen way to introduce stepwise the handling of these systems to fulfil the needs of the

international employment market and to provide a practical focus within the education. Effective teaching

concepts have to improve this situation by considering the pedagogical and didactical aspects, which

supports the individual learning process of each student. Our research idea in this contribution considers

actual needs of higher education, e.g. present learning in a lab as well as e-learning courses supported by

new methods in Technology Enhanced Learning by recording student’s behaviour to guide him through the

system. Therefore we introduce an adaptive learning model which considers tracking and analyzing results

deduced with methods of Application Usage Mining and built up a new idea to improve the learning

progress. Within this adaptive learning model we propose an adaptive learning environment to bring

learners and supervisors together to achieve positive influences on learner’s behaviour and the learning

progress.

1 NEED FOR CHANGE

Knowledge transfer is a key factor of our

international oriented and globally connected

education system in which universities and higher

education institutions have to survive. Therefore

these institutes have to collaborate with similar

providers in different countries to compete in the

learning market. This leads to a redefinition of their

internal and teaching processes and an adaption of

their curricula to the actual needs of the employment

market. Higher education institutions have to

support the individual learning lifecycle based on

flexible learning services. Universities appear as

“knowledge centers” for lifelong learning and have

to be more flexible then in the past. The beginning

of virtualization demands personalised and flexible

learning services, whenever the learner needs and

wants to access them. These services become an

essential part of his lifelong learning.

Information and communication technologies

(ICT) are often used as an enabler to support these

processes. Technology Enhanced Learning (TEL)

e.g. allows effective and cost-efficient learning

environments based on individual needs and in a

personalised way. TEL is focusing on the

technological support of any pedagogical approach

that utilizes technology and encompasses virtual and

physical technology enhanced learning

environments (incorporating physical learning

spaces, institutional virtual learning environments,

personalized learning environments and mobile and

immersive learning environments). The aim of TEL

is to explore and develop effective practice in the

delivery of flexible, seamless and personalised

services to learners, focussing on the technological

interface between the learner and their learning

environment. Therefore learning activity consists of

learning resources, actions, context, roles and the

learning objective to support the learner to his

learning goals, respecting individual as well as

organizational learning preferences.

521

Peters D., Haak L. and Marx Gómez J. (2010).

LEARNER-ORIENTED APPROACH FOR ENTERPRISE SYSTEMS IN HIGHER EDUCATION USING TEL-BASED CONCEPTS - Research Positioning

Paper.

In Proceedings of the 2nd International Conference on Computer Supported Education, pages 521-526

DOI: 10.5220/0002874105210526

 SciTePress

The technology plays an important role in

supporting all these activities. That is surely one

reason why the European Union (EU) support a

number of project in this area, e.g. within in the 6th

framework the Network of Excellences PROLEARN

(www.prolearn-project.org) and Kaleidoscope

(www.noe-kaleidoscope.org) which have the main

objective to have shape the research area around

TEL. In this research environment we want to

introduce our new concept for teaching Enterprise

Systems (ES) in higher education.

Due to the actual needs of the employment

market, Enterprise Systems are getting more and

more important for the educational environment.

Though, the interferences and complexity of the

different perspectives in computer science, business

economics and the technology aspects make

teaching and learning quite difficult in this field.

Students need to be taught on practically approved

systems to develop their own practical experience

besides the theoretical lectures. Therefore ES offer

the capability for future pedagogic innovation within

higher education, which results from the possibilities

in illustration, visualization and simulation of

business and decision-making processes to students

(Ask et al., 2008).

This contribution introduces an approach, which

presents how technologies like Application Usage

Mining (AUM) could improve the teaching of ES in

higher education. Our research interests consider

ERP-technologies and their usage in adaptive

learning environments in higher education.

Furthermore we focus besides actual standard

software on new concepts resulting from up-to-date

research, e.g. Federated ERP (FERP)-Systems

(Brehm et al., 2009).

2 LEARNER ORIENTATION

Case studies are not the only a method for a

successful learning process design; there are still

problems occurring from missing background

information as well as from differences in the

domain knowledge of the learners. The actual

teaching material does not reflect the different

education and major studies of the students; it is the

same for all, equal whether they are studying e.g.

economics, computer science or pedagogic. Our

research approach follows the idea to utilize new

technologies from the wide range of TEL to reform

these education methods and to guide the learner

through his learning process: we call this Learner

Orientation.

The main idea of our approach is to put the

learner’s behaviour in the focus of interest. This

approach is not new (e.g. (Lenz, 1998)) and used in

many parts of continuing education for adults. The

orientation to the individual replaces the principle of

orientation to the participants which concentrates on

bringing participants into the institution of adult and

continuing education. This development is resulting

from the fact that traditional educational systems are

not considering the learner’s needs. By gearing to

the learner and his behaviour the learning process

deals with all aspects of the individual and leads to a

higher individualization of learning. The result is a

higher self-organized and independent learner. This

is the main reason why it is mainly used on

continuing and adult education. One result from this

is for instance the well-known method of Tandem

Learning, a method where two learners improve

their learning progress in a team and through

exchanging each other.

In the following section we reflect the problems

which occur especially in the area of ES in higher

education and present our technical oriented

approach to improve the learning progress in the

educational area. The aim is provide a technical

solution to consider the personal learning process

and progress to improve the teaching material and

teaching methods. It is a new method to give the

teacher a feedback about the individual problems of

the learner within the material and the tasks itself to

enhance the whole education in this field of ES in

higher education.

3 ENTERPRISE SYSTEMS IN

HIGHER EDUCATION

Higher education utilizes ES (e.g. Enterprise

Resource Planning (ERP)-Systems) or Business

Intelligence Systems to prepare students for the daily

routine in their working life and to provide them a

practical experience in the application of these

technologies. This is often supported by software

developing companies like SAP® or Microsoft®,

which also have an interest in getting the user,

developer and manager of tomorrow in an early

touch with their software products.

A common method for teaching ES like ERP-

systems is the usage of case studies. Leading

software companies like SAP® or Microsoft®

provide customized environments in form of

customized companies (e.g. the International

Demonstration and Education System (IDES) by

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522

SAP® and the Cronus AG by Microsoft®). For

supporting these activities the SAP AG build up an

own higher education competence network in form

of the University Competence Center (UCC) in

Magdeburg and Munich based on the SAP

University Alliance® programme. Besides, they

offer teaching material in form of case studies,

mostly based on material used for the origin

software training courses. These courses give an

overview and more or less detailed impressions of

the system functionality, but often lacks in missing

background information about company structures

and processes.

Though, this concurrent interests have to be

considered and the missing of pedagogic and

didactic aspects need to be improved and

implemented. For an effective usage of case studies

it is necessary to give the learner the chance to find

his own solution, to consider strategic aspects and to

make reasonable decisions. Therefore the case study

design is already a critical success factor (Hans et

al., 2008).

Besides improving this case study material we

want to provide a technical solution based on the

user interaction within the system.

4 IMPROVEMENT OF THE

LEARNING PROGRESS

As mentioned before, today’s business application

systems are mainly focusing on the integration of

different enterprise sectors within one enterprise or

across multiple enterprises. In the best case the

solution is an all-round product which covers all the

functionality a modern enterprise is dealing with. As

a negative side-effect the user faces a rising

complexity and an enormous amount of navigation

and handling opportunities within these systems.

This is one reason why it is becoming more and

more difficult for users to handle such complex

systems in an appropriate way (Haak et al., 2009).

Our superior aim for the identification of the

learner’s behaviour is the deduction of the current

state of knowledge and the system-familiarity of the

user from his executed tasks and steps he performs

during the work within the system. A schema which

illustrates our idea of the improvement of the

learning progress is visualized in Figure 1.

On the basis of logging and tracing information,

which is permanently recorded by the system, we are

able to analyze the behaviour patterns which also

includes specific deficits or general problems a user

Figure 1: Improved Learning Process.

has in performing his ES-supported work. We can

use this information to categorize different user

types depending on their knowledge level. Finally,

the learning material can be modified, according to

the learner’s knowledge category. In a dynamic

monitoring, the results of the tracking and analyzing

phase, which lead to a tailored course material, can

be tracked again to close the circle. Future behaviour

patterns will be tracked and analyzed in the same

way once again, in order to improve the learning

progress step by step.

The schema itself will be described in detail in

the following sections. The tracking and analyzing

part, which is supported by existing approaches, is

explained in Section 4.1. Recognizing these patterns,

we can identify possible problem solutions or

improvements in specific domains in a technology-

enhanced way, in order to improve the knowledge

and the performance of the individual user. The

enhancement can be realized on top of the tracking

and analyzing results. This improvement and its

influence on the learning process is explained in

Section 4.2.

4.1 Tracking and Analyzing with

Application Usage Mining

Regarding the new technological possibilities to

track the learner’s behaviour in ES, such as ERP-

Systems e.g., we can benefit in our work from the

existing AUM approach (Kassem, 2007). The user

leaves traces in the systems which are logged via

trace files and protocols. This tracking information

is a record of the performed steps or fulfilled tasks

of the user in the system. According to Figure 2, the

structure of such a User-Trace-File in the SAP R/3-

system for example contains the name of the

executing user, the code of the performed

LEARNER-ORIENTED APPROACH FOR ENTERPRISE SYSTEMS IN HIGHER EDUCATION USING TEL-BASED

CONCEPTS - Research Positioning Paper

523

Figure 2: User-Trace-File in SAP R/3.

transaction (VA01 for Create Sales Order), the input

values to the specific input fields (0001 for Sales

Organization), the transaction time via time stamps

and different other things.

The AUM idea is based on the well-established Web

Usage Mining (WUM) which is dealing with the

analyses of the user’s behaviour in the field of web

applications (Srivastava et al., 2000; Spiliopoulou,

2000). Defining AUM, Kassem pointed out several

differences between web applications and business

application systems in order to outline his approach.

While browsing the Web, the user has an

anonymous access to a web site, a user in a business

application system has to identify oneself by using a

log-in and his personal password. Another difference

is that a visitor of a web site does typically not need

an authorization in order the access the content,

whereas the user of a business application system

has a certain authorization, according to his function

in the enterprise in order to perform his assigned

tasks. Furthermore another difference is the user’s

behaviour and the objective, which is completely

free or undefined during the visit of a web site, while

a user of a business application system has to

perform predefined tasks according to a business

process, which have to be executed efficient and

with an optimal performance (Kassem et al., 2003).

Data Mining, Process Mining and Workflow

Mining, as other approaches in this field which also

need to be taken into account, are also playing a role

in this context. While Data Mining is the basis of all

these approaches, it deals with the creation of

knowledge out of large data amounts. Therefore

Process Mining uses the knowledge of processes and

extracts data, which describe the execution of

processes in order to model, save and reuse the

process knowledge (Schimm et al., 2003). Workflow

Mining controls, improves, executes and monitors

business processes and aims on the extraction of

information about processes from transaction logs

for the purpose of visualizing the current status of a

workflow model (Zur Mühlen and Hansmann,

2005).

Another approach is the Education Data Mining

(EDM), which is defined as the process of

converting raw data from educational systems (such

as interactive learning environments, computer-

supported collaborative learning, or administrative

data from schools and universities) to useful

information that can be used by educational software

developers, learners, teachers, parents and other

educational researchers. EDM is also an emerging

discipline, concerned with developing methods for

exploring the unique types of data that come from

educational settings, and with using those methods

to better understand the learner (Baker et al., 2008).

This information can also be used by the adaptive

learning environment, which is introduced in the

next section, in order to influence the learner’s

behaviour as well as on the learning progress itself.

4.2 Influences on Learners Behaviour

and the Learning Progress

The results of the tracking and analyzing phase,

supported by AUM, built the basis for our new

approach of a learner-orientation. According to

Figure 3, the adaptive learning model shows how

supervisor and learner are connected to the adaptive

learning environment.

Figure 3: Adaptive Learning Model.

The adaptive learning environment is based on a

Business Process Platform which represents

processes within an enterprise. Exercises will be

generated according to the underlying business

processes. This helps the learner to understand the

functions which are covered by the business

application system. It is also visible that supervisor

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and learner are interacting with the adaptive learning

environment. This interaction is described in the

following.

For example, a learner who wants to fulfil a

specific task according to his exercises within the

system leaves a mark which can be expressed in a

graph or a path. Kassem is using Petri nets to

visualize these paths for the analysis of the data. In

our approach the adaptive learning environment

possesses a predefined workflow structure which

contains the “correct” path of fulfilling this task or

exercise. These paths can also be visualized with

other process description languages like Event-

driven Process Chains (EPC) for example.

An imaginable exercise can be the creation of an

order with more than one order item in the system.

In Figure 4 a Petri net illustrates the SAP transaction

Create Order. In the first state A the learner has to

enter the first order item for the order. After entering

an item number and the required amount, the learner

can complete the order with a confirmation in state

B. If he wants to add additional order items, the user

reaches state C. He can enter more order items and

then complete the order, which leads him in state B

finally. In comparison with the transaction workflow

of a learner, it is possible to find out, if the learner

could complete the task in accordance to the task of

the exercise. If the learner had problems in finding

the right button to add additional items to the order,

his path does not have a state C. In this way, the

adaptive learning environment can propose a hint in

order to help the learner in completing the task.

Moreover it could be assumed that the user

obviously needs help if he spends too much time in

state A.

Figure 4: Petri Net of the SAP Transaction Create Order.

The way of assistance how the adaptive learning

environment supports the learner, depends on the

exercise itself and the knowledge level of the user

which was captured by the system. Both parts can be

influenced by the supervisor.

The proposed solution of the adaptive learning

environment will improve the learning progress

because of different reasons. The mentioned benefits

from a didactical point of view have been introduced

in the first chapters. Nevertheless, the technical

realization offers more benefits for learners and

lecturers, e.g. it is possible to deal with each single

problem of an individual learner. The system could

offer different ways to get to the solution or

recommend related literature. In general, the

proposed solution can bring a lot of advantages to

the participating parties like the learners itself, but

also to the associated lecturers. Each group of

learners is associated to a supervising person, which

is normally represented by a teacher or lecturer of an

educational institution. In the traditional way, an

often unequal knowledge level of the learners exists.

The learners have different methods of learning and

the supervisor needs to respond to each one

individual. This is often very time consuming and

can mostly not be realized in practice. As a result we

can assume that the existing ways to identify the

learner’s behaviour are not appropriate to fulfil

today’s requirements in the field of handling ES.

It is also imaginable that different learners who

are working on the same exercise can benefit from

each other. Experienced learners can assist learners

who do not have the same experience. This scenario

is also supported by the adaptive learning

environment. Via the comparison of the solution

paths from different learners the system can identify

similar problem groups or learners which can help

each other in a successful way. If there is a learner

who already completed the task after having the

same issue, he might be the best contact person.

Furthermore the comparison of solution paths

can be used to find out whether there is general

problem concerning the content of the exercise. In

this case, if the majority of the learners have the

same issue which makes a positive completion of the

task impossible, there might be a deficit in the way

an exercise is putted. In this case the supervisor will

be informed about the appearing problem. As a

result it could be necessary to improve or rethink the

teaching tasks and methods. When talking about the

tracking and the further processing of the learner’s

progress, we need to take privacy issues into

account, which are not analyzed at this early step of

research.

5 CONCLUSIONS AND FUTURE

WORK

In summarization, the teaching of ES in higher

education is a young discipline, which has to be

improved to fulfil the needs of today’s students. The

LEARNER-ORIENTED APPROACH FOR ENTERPRISE SYSTEMS IN HIGHER EDUCATION USING TEL-BASED

CONCEPTS - Research Positioning Paper

525

learning process has to be more flexible and

individually customized to the background of the

student and to the needs of global employment

market. Therefore we focus on the concept of

Learner Orientation and design a concept to improve

the teaching of ES in higher education supported by

a technical solution which considers the knowledge

level of each individual learner.

The introduced AUM delivers techniques to

identify the behaviour of a user in an ES. Therefore

it uses the transaction data which is tracked during

the interaction of the user with the system and is

stored in trace- and log-files for further analysis. Our

proposed adaptive learning environment, as a major

part in the adaptive learning model, can analyze the

user’s behaviour and draw conclusions to the

knowledge level and possible problems during the

work. Then, it can deduce problem solutions on the

basis of the analyzed data and assist the learner in

completing his task. Besides the learner, the adaptive

learning environment can also assist the supervisor

or lecturer of a group of learners. Thus, an

improvement of the learning process including all

participating parties can be assured.

In future the architectural design has to be

formulated in much more detail. The different

components of the adaptive learning model have to

be more concrete and well defined. After this, a first

technical implementation of a prototype will be

focused. Therefore it is necessary to identify the

specific requirements and distinguish the parts

which definitely have to be realized. In the end, an

evaluation of the success and the major

improvements in comparison to existing approaches

will be carried out.

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