A Knowledge Map Tool for Supporting Learning in Information Science

Helmut Vieritz

, Hans-Christian Schmitz

, Efﬁe Lai-Chon Law

, Maren Scheffel

Daniel Schilberg

and Sabina Jeschke

Institute of Information Science in Mechanical Engineering, RWTH Aachen University,

Dennewartstr. 25-27, 52068 Aachen, Germany

Fraunhofer Institute of Applied Information Technology FIT, Schloss Birlinghoven, 53754 Sankt Augustin, Germany

Department of Computer Science, University of Leicester, University Road, Leicester, LE1 7RH, U.K.

Keywords:

Knowledge Map, Large Classes, Self-regulated Learning, Higher Education, Information Science.

Abstract:

Large classes at universities (>1600 students) create their own challenges for teaching and learning. Audience

feedback is lacking and ﬁne tuning of lectures, courses and exam preparation to address individual needs

is very difﬁcult to achieve. At RWTH Aachen University, a course concept and a knowledge map learning

tool aimed to support individual students to prepare for exams in information science through theme-based

exercises were developed and evaluated. The tool was grounded in the notion of self-regulated learning with

the goal of enabling students to learn independently.

1 INTRODUCTION

The Institute of Information Management in Mechan-

ical Engineering (IMA) of the RWTH Aachen Uni-

versity (RWTH) offers a lecture about information

science in mechanical engineering (see ﬁg. 1) that

is combined with a lab, a group exercise and exam

preparation courses. The lecture focuses on object-

oriented software development and software engi-

neering (more details in (Ewert et al., 2011)). In a pre-

vious semester more than 1600 students attended the

lecture. It received good evaluations from students as

well as staff. This feedback was taken into account to

revise the lecture, the lab and the courses a little fur-

ther for the summer term of 2012. Here are some of

the challenging questions of the revision: (a) How can

the student’s learning process be supported in a better

way? (b) What are the main obstacles the students

face when learning programming concepts and tech-

niques of object-oriented programming and software

engineering? (c) Which resources are needed to im-

prove the learning process and are these available? (d)

How can student-by-student communication be used

for peer instruction to relieve the tutors?

The e-learning system L2P

of the RWTH is al-

ready widely used as a Learning Management Sys-

tem (LMS) in the lecture, the group exercises and

http://www2.elearning.rwth-aachen.de/english

Figure 1: Lecture for information science in mechanical en-

gineering

David Emanuel.

the lab. However, additional learning support was re-

quested to assist students in and out of class, but par-

ticularly when learning autonomously. Therefore, a

Web-based e-learning test bed was designed and im-

plemented which supports different kind of learning

situations as autonomous learning, peer-instruction

learning as well as e-mail support by tutors. It ex-

tended the L2P learning room with interactive and au-

tonomous learning capabilities.

Additionally, a tool test bed evaluation was de-

signed to analyse how the test bed impacts the stu-

dents’ learning processes. Some research questions

addressed were: (a) Are the students willing to use

717

Vieritz H., Schmitz H., Law E., Scheffel M., Schilberg D. and Jeschke S. (2013).

A Knowledge Map Tool for Supporting Learning in Information Science.

In Proceedings of the 5th International Conference on Computer Supported Education, pages 717-723

DOI: 10.5220/0004451907170723

 SciTePress

interactive e-learning tools? (b) Is the students’ feed-

back to the teaching staff supported by the test bed,

e.g. regarding learning interests and obstacles? (c)

Is the test bed capable to support students and tutors

in the learning and teaching process? (d) How can

the additional challenges of large classes (user man-

agement, anonymity etc.) be managed within the test

bed?

The rest of the paper is structured as follows: Sec-

tion 2 will describe the general course design. In

section 3, related research is discussed, followed by

an explanation of the self-regulated learning concept.

Then, the ROLE environment will be introduced (sec-

tion 4). Finally, in section 5 we will present the eval-

uation and conclude in section 6.

2 COURSE CONCEPT

The lecture period of the summer semester 2012

started in April and ended in July, followed by a time

of exam preparation courses starting in September.

The time between these two blocks was used for au-

tonomous, self-regulated learning (SRL). The envi-

ronment for individual exam preparation was imple-

mented consisting of three ROLE (Responsive Open

Learning Environments) widgets, namely a knowl-

edge map, a chat widget and a history widget. In the

lab students were able to experiment and actively ap-

ply the fundamentals of object-oriented programming

with Java. It took place together with the lecture dur-

ing the summer term from April to July (see ﬁg. 2).

The exam preparation courses in September offer the

students the possibility to train the addressed compe-

tences in smaller audiences.

In addition to renewing the lecture format, the

course organisation was updated and supplementary

digital material was provided to the students via

Figure 2: Schedule of lecture, group exercise and lab during

the summer term 2012.

the RWTH learning management system L2P. The

course’s L2P was then enhanced by a selection of

ROLE

widgets, more speciﬁcally by widgets sup-

porting self-regulated learning (SRL). Furthermore,

another Technology Enhanced Learning (TEL) aspect

was introduced into the course by adding a Personal

Response System (PRS) sometimes also described as

an Audience Response System (ARS). This TEL tool

complemented the ROLE technology as it enhanced

the opportunity of further active learning prospects

for students and also offered an increased interactive

setting in terms of the pedagogical delivery.

Previous student evaluations had shown a demand

for more self-contained programming occasions as

well as practical ”hands-on” tasks to try out. The

newly designed lab sessions thus offered palpable

tasks that the students could carry out completely on

their own. The setup for these object-oriented pro-

gramming lessons was based on working with LEGO

Mindstorms NXT (see ﬁg. 3) robots for use by large

classes. To support the Java programming language

implementation on the NXT controller, LeJOS was

used (Solorzano, 2001).

Figure 3: Model of the LEGO Mindstorms NXT robot used

in the laboratory (Ewert et al., 2011).

The RWTH ROLE test bed work in 2012 was initi-

ated with a Web-based survey that aimed to collect

details about the students experience with e-learning

and SRL at the beginning of the lab in April 2012.

The ROLE widget environment was introduced to the

students during the second week of their studies. The

enriched ROLE-based learning environment offered

additional support for improvement in SRL opportu-

nities. It also provided particular information about

programming in general, related tools, modelling, as

well as Java itself. Around 1,600 students participated

in the course. All students were informed about the

http://http://www.role-project.eu/

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718

ROLE-enhanced learning environment offer via sev-

eral announcements during lectures and labs and via

email. During the standard midterm teaching evalua-

tion, a short ROLE-related survey was issued. At the

end of the lecture period, the ROLE test bed was also

adapted for individual exam preparation during sum-

mer time. Finally, after the exam educational staff

was interviewed to evaluate the environment and its

application within the course.

The lab sessions took place in the largest computer

pool of the RWTH which is equipped with approx-

imately 200 workstations. This, however, restricted

the maximum number of students that could attend

the lab in parallel to 200 students who then worked

with 100 Mindstorms NXT robots. Since those 100

robots could not be dismounted and reassembled in

each lesson, the lab was based on a standardised and

pre-assembled robot model as depicted in ﬁg. 3. This

allowed for several student teams to work with the

same robot set in consecutive classes and improved

the comparability of the students’ achievements. (To

increase motivation, it would have been desirable that

each team had their dedicated construction set. How-

ever, this would have resulted in an order of 750 robot

construction kits.)

The second part of the lab sessions was based on

the principle of problem-based learning. The stu-

dents were requested to program a robotic gripper

inspired by industrial robots. This resemblance to

”real” robots was meant to result in a better under-

standing of mechanical engineering principles by the

students. The assigned task was to get the robot to

scan their surrounding area for coloured balls, picking

them up and putting them into a box. In order to get

the robots to detect the balls, students could make use

of an ultrasonic sensor, a light sensor and a touch sen-

sor located within the gripper. The robot arm could

be moved up and down as well as left and right by di-

rectly controlling the corresponding motors. The third

motor controlled the gripper hand. The students im-

plemented this task during the remainder of the lab.

To allow for progress tracking and giving weaker stu-

dents a chance to catch up, the overall goal was sepa-

rated into four sections as described below.

3 RELATED RESEARCH AND

SELF-REGULATED LEARNING

The presented approach addresses different recent re-

search issues such as teaching and learning in large

classes as well as using cloud services and Web 2.0

applications for e-learning support. The challenge of

teaching large classes has been a research issues for

many years (cf. (Leonard et al., 1988; Knight and

Wood, 2005)). The more technical background of

building e-learning tools from Web 2.0 components is

being discussed in (Palmr et al., 2009). The approach

uses six dimensions for the mapping of Web 2.0 ap-

plications to personalised learning environments. The

capabilities of ROLE-based cloud learning services

are investigated in (Rizzardini et al., 2012). The eval-

uation shows that cloud-based learning support with

ROLE environments is possible but the learners may

need introduction and time to be familiar with interac-

tive e-learning tools. The particular aspect of naviga-

tion guidance for learning questions in Java program-

ming is discussed in (Hsiao et al., 2010).

Self-regulated learning (SRL) denotes a learning

process where the learner herself decides what to

learn, when and how (Zimmerman, 1998). Different

scholars have attempted to develop SRL models such

as the ﬁve-component SRL model of (Efklides, 2009),

which comprises cognition, meta-cognition, motiva-

tion, affects, and volition.

SRL is a central pedagogical focus for higher ed-

ucation in general and the project ROLE in particu-

lar. SRL empowers the learners to manage their own

learning irrespective of organisational interventions.

According to (Steffens, 2006), the quality of learn-

ing outcomes varies with the extent to which learners

are capable of regulating their own learning. In addi-

tion, SRL is considered a core competency for a pro-

fessional career because of several reasons. Firstly,

to keep abreast with the rapid social and technical

development of a dynamic society requires life-long

learning skills, which entail high autonomy. Sec-

ondly, the border between working and learning is

getting blurred: we learn while we work by resolv-

ing issues in the workplace and we work while we

learn by directly applying what we have learnt; SRL

skills enable us to integrate seamlessly the knowl-

edge and experience from both realms. Thirdly, it

has been shown that self-regulation improves learn-

ing outcomes (Steffens, 2006).

Nonetheless, the advantages of SRL can only be

realised provided the learner is able to follow a SRL

approach. Self-regulation manifestation is a contin-

uum rather than all-or-none. It ranges from an entirely

independent pursuit for knowledge and skills to a

structured coaching with a teacher working alongside

with a learner. In the latter, it could be challenging

for both teachers and learners. Amongst others, some

salient issues include: learners are not accustomed to

deciding learning goals for themselves and thus need

some even highly structured guidance; teachers might

not be prepared to give freedom to learners while they

are still held responsible for their learning progress;

organisations might not be prepared to engage learn-

AKnowledgeMapToolforSupportingLearninginInformationScience

719

ers and teachers in learning scenarios that are rela-

tively open, rendering accreditation or any kind of for-

mal assessment of learning outcomes difﬁcult.

Speciﬁcally, in ROLE, the SRL process model

is deﬁned as a learner-centric cyclic model consist-

ing of four recurring learning phases (see ﬁg. 4):

(i) learner proﬁle information is deﬁned or revised;

(ii) learner ﬁnds and selects learning resources; (iii)

learner works on selected learning resources; and (iv)

learner reﬂects and reacts on strategies, achievements

and usefulness (Fruhmann et al., 2010).

Figure 4: The SRL concept (Fruhmann et al., 2010).

To enable the fulﬁlment of these learning phases, a

learning environment and sets of learning activities

should be provided where learners can practice how to

learn in a self-regulated manner. The aforementioned

learning environment can provide additional learning

material (knowledge map) that can be browsed inde-

pendently, provide help by lecturers and tutors, pro-

vide communication channels to exchange with oth-

ers. That is, support plan and learn. Evaluating the

extent to which the students acquire the SRL skills in

this way can effectively be measured through a well-

designed survey.

4 THE ONLINE LEARNING

ENVIRONMENT

In the test bed there are three ROLE widgets: the Web

2.0 Knowledge Map widget (WKM, (von der Heiden

et al., 2011), see ﬁg. 5), the chat widget and the his-

tory widget. The test bed scenario was deployed for

the lab and also for the individual exam preparation

of the students in August and September.

The WKM aimed to provide the students with in-

formation covered in the lecture and the lab. It was

ﬁlled with additional SRL-adapted content thus fo-

cusing on typical SRL situations such as the exam

preparation phase. It contained explanations and mo-

tivations for notions, deﬁnitions or examples, e.g. for

basic Java programming constructs. Background in-

formation, e.g. about the installation and usage of

the Eclipse programming environment, was provided

as well. Exercises for exam preparation were asso-

ciated with content. These entities of content are

called knowledge objects. The presentation and or-

ganisation of the WKM followed the paradigm of

object-oriented analyses and design in software devel-

opment. Relations between objects and classes of ob-

jects were visualised (see ﬁg. 5) to underline knowl-

edge associations. Functionalities for annotations, re-

marks and feedback were provided to support indi-

vidual SRL. For the ﬁrst time in the course’s history,

the WKM gave students an opportunity for individual

support during their time of exam preparation.

The second widget, a chat widget, was embed-

ded to offer students the possibility to ask and answer

topic-related questions. Other students answered the

posed questions and, additionally, a tutor also moder-

ated the chat. Finally, a history widget was embedded

into the learning environment. It supported the back-

ward navigation within the environment by offering

the last ﬁve activated knowledge objects. Based on

inter-widget communication (IWC, (Renzel, 2011)),

the widget used data from the WKM widget to sup-

port the learner with his or her own learning history.

The WKM was maintained by the IMA, the test bed

was hosted by the department of information science

at the RWTH and access to the WKM was granted via

the login for the lab.

Figure 5: Screenshot of the RWTH WKM (start page).

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720

5 EVALUATION

The ROLE environment was used to some extent dur-

ing the lab time from April to June. Usage has grown

signiﬁcantly some weeks before the exam in Septem-

ber when the students started their individual prepa-

ration. Additionally, the existence and purpose of the

learning tools were announced by an email to all stu-

dents. The access peak was reached in the days just

before the exam when students switched to ”power

learning”. This is illustrated by ﬁg. 6 showing the

number (by day) of accessed knowledge objects. A

knowledge object is a small piece of content as a no-

tion explanation or an exercise. Figure 6 thus un-

derlines the exam-oriented learning during the exam

preparation that restricts the leeway in learning and

thus the autonomy of the learner. The e-learning en-

vironment consisting of knowledge-map, history and

chat enables independent and cooperative learning.

Moreover, it offers learning ﬂexibility since the en-

vironment is accessible at any time; students can use

it outside the course hours.

Figure 6: Requested knowledge objects by day.

In June 2012 before the summer break (i.e. at the

end of the lab session but before the exam prepara-

tion), the students were asked about the usefulness

of the e-learning environment and rated it positively.

162 stated that the application of the computer-based

learning environment was useful. On the given scale

from 1 (strongly disagree) to 5 (strongly agree), the

arithmetic mean of the results was 3.7 with a stan-

dard deviation of 1.3. Since 3 would be neutral, the

students evaluate the environment positively without

being stunned.

After the course, the environment has been eval-

uated by the teaching staff. We conducted four in-

terviews. Three of them with student assistants who

acted as tutors within the practical exercise and the

exam preparation and who were also responsible for

adding contents to the knowledge map and solving

technical issues. One interview was conducted with

the lecturer who was responsible for the overall coor-

dination and involved in the planning and conception

of the whole course.

In the interviews we asked the participants to rate

several statements on a scale from 1 (strongly dis-

agree) to 5 (strongly agree) and explain their rat-

ings. Moreover, we asked them to comment on the

strengths and weaknesses of the environment and to

suggest improvements. The students’ positive judge-

ment of the environment has been corroborated by

the teachers. For each statement the arithmetic mean

(AM) and the standard deviation is given (SD) (in in-

terpreting these measures one has to keep in mind that

only 4 persons rated the statements):

• The environment was useful for the students. AM:

4.25, SD: 0.43

• The environment was useful for me in my role as

a lecturer/ tutor. AM: 4.00, SD: 0.71

• The students reached the learning goals better be-

cause of the environment. AM: 4.00, SD: 0.71

• I reached my teaching goals better because of the

environment. AM: 3.50, SD: 1.12

• I would advice the students to use such environ-

ments more often if they had access to them. AM:

4.75, SD: 0.43

• I would use such environments more often for

teaching if I had access to them. AM: 4.67, SD:

0.47

• I would use such environments more often for

learning if I had access to them. AM: 3.25, SD:

1.79 (This is an interesting result: Why do the lec-

turers / tutors rather advice their students to use

such an environment than use it themselves? The

Interviewees answer that their personal learning

style is not optimally supported by such an envi-

ronment, because ﬁrstly they prefer not to browse

through learning contents but to study text books

and other material, in particular exercises and

exam questions from previous semesters, from be-

ginning to end. Secondly, they prefer using pen

and paper over doing all exercises with the com-

puter. Therefore, they request an export to PDF so

that they can print selected parts of the material.

• I consider the environment used within his course

as a didactically sound means. AM: 4.50, SD:

0.50

According to the interviewees, the strengths of the

environment were, ﬁrstly, that the knowledge map

gave a clear overview on the course contents and

their inter-relationships. The students got a starting

point for browsing through the material and explor-

ing the themes independently. Questions could be an-

swered by pointing to speciﬁc objects on the knowl-

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721

edge map, and students could (and did) answer their

follow-up questions themselves by exploring the sur-

rounding/linked objects. Thereby, the autonomy of

the student was effectively supported. Secondly, the

chat widget allowed fast feedback from the students.

Questions could be immediately answered. Since all

students could read the answers, questions did not

have to be answered twice. Thereby, the tutors’ expla-

nations became more efﬁcient. The tutors saved time

for helping with truly individual problems. Thirdly,

the environment improved the communication among

the students and thereby collaborative learning. After

a short time span the students began to answer ques-

tions of other students. Fourthly, the environment ren-

dered the students more ﬂexible regarding their time

management and learning speed. They were able to

repeat lessons and exercises without losing track of

the course or thwarting others.

Concerning the weaknesses, the interviewees

found technical and usability issues, in particular re-

garding the administration of the environment and the

adding of new contents to the knowledge map. These

issues have to be solved but do not affect the concept

and general design of the environment. Moreover, the

interviewees propose the following extensions of the

environment:

• The chat widget should be exchanged or supple-

mented by a forum for general questions and by

a commentary function for the elements of the

knowledge map. This would improve the linking

of contents with questions and comments.

• They consider a learning planer, consisting of a

simple to-do list with links to exam-related ma-

terial and topics, self-tests and a visualisation of

the current level of knowledge/ exam preparation

progress (related to the self-test results) as ex-

tremely useful.

• The interviewees agree that the contents are the

most important feature of the environment. These

have to be updated regularly.

• So far the contents of the knowledge map are ex-

plored by browsing. An additional search engine

for the direct search of speciﬁc content would be

reasonable.

• One interviewee deems a recommender system

that recommends related external material useful.

One aim of offering the ROLE environment was to

support SRL. Has this goal been reached, that is, did

the environment effectively support self-regulation?

The interviewees claim that this is in fact the case.

While in the beginning a lot of trivial questions were

asked, the students were able to ﬁnd the answers to

such simple questions themselves soon. (The ques-

tion is, however, whether we can attribute this devel-

opment to an improvement of self-regulation or rather

to a learning effect regarding the course contents.)

The interviewees considered it important to sup-

port SRL. They estimated that by far most of their

students had medium SRL-level. They correlated

the SRL-level with the general knowledge level and

acknowledged that students with a high SRL-level

learned better and faster. However, as tutors and lec-

turers they generally preferred to teach students with

a medium SRL-level over students with a high SRL-

level. They justiﬁed this preference as follows:

• A tutor was supposed to lead interesting discus-

sions with high SRL-level students. However,

they did not need a tutor that much and therefore

did not get in close contact to them. Teaching of-

ten did not really take place. Moreover, these stu-

dents tended to be good students that asked difﬁ-

cult questions. A teacher had to be well-prepared

and feel certain on the course topic to cope with

these questions. This made it sometimes harder to

teach students with a higher SRL-level.

• Medium SRL-level students were intelligent but

still requested interaction with a teacher. The

teacher got in contact with them, observed the

learning progress and saw the positive effect of

explanations and assistance. The interviewees

found this very rewarding.

• The interviewees considered that a low SRL-level

is correlated with rather low learning success.

Teaching students with a general low level was

considered to be cumbersome and not very re-

warding.

Feedback given through the environment was recog-

nised by teachers as very important. The intervie-

wees emphasised the role of the chat (or a forum).

Feedback was deemed important for estimating the

students’ progress and thus adjusting interventions.

Moreover, it makes teaching more satisfying.

6 CONCLUSIONS

A course design for information management in me-

chanical engineering was presented. The course had

been re-designed to better support SRL. Therefore, an

e-learning environment with several ROLE widgets

was provided to the students. The environment aimed

to support individual exam preparation. In compar-

ison to the lecture of 2011, the evaluation showed

the necessity of intensive promotion for new and ad-

ditional e-learning tools. Tool objectives and ad-

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722

vantages must be clearly communicated (at the right

time) to the students. Nevertheless, only a minority

of all students had used the test bed for a longer time.

Here, guidance with learning questions as in (Hsiao

et al., 2010) may motivate students and foster com-

munication. Until now, overview and learning guid-

ance is given by the visualisation of topic relations on

the start page, the hierarchical and object-oriented or-

ganisation of knowledge in the map and the linking of

knowledge objects.

To take stock, the evaluation of this test bed has

shown that the environment supports SRL and col-

laborative learning in large classes. The answering

of student questions was easier via the chat widget

than by email as all students were able to see the

answer. Additionally, the chat fostered student-to-

student support. Even if the test bed offered support

for early learning, the peak of usage was reached just

before the exam. It indicates the students’ remaining

in power learning.

The test bed was implemented as a cloud learn-

ing application combining widgets as services in an

overall application and using IWC for communication

between the widgets. Since different people were re-

sponsible for the particular widgets, it was sometimes

hard to ﬁx problems e.g. when server were not acces-

sible.

Until now, the test bed was aimed to demon-

strate the possibilities of ROLE technology in large

classes. The demonstration was successful and fur-

ther development has to focus more on the learn-

ing requirements of students. Therefore, future im-

provements are seen in better communication and

feedback support to strengthen e.g. learning motiva-

tion. Suggested improvements are ﬁrstly better col-

laboration support by adding improving topic-related

communication (forum, notepad linked to contents

of knowledge map) and secondly better SRL-support

by adding a learning planer that supports planning

(to-do list) and reﬂection (self-tests, visualisation of

progress). The offering of learning strategies such

as learning questions (Hsiao et al., 2010) within the

learning tool may offer new advantages and motiva-

tion for the students.

ACKNOWLEDGEMENTS

The research leading to these results has received

funding from the European Community’s Seventh

Framework Programme (FP7/2007-2013) under grant

agreement no 231396 (ROLE project). Additional

funding at the RWTH Aachen University was re-

ceived from the Federal Ministry of Education

and Research (BMBF) for the project Excellence

in Teaching and Learning in Engineering Sciences

(ELLI project).

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