Reﬂections on Teaching Electrical and Computer Engineering Courses at

the Bachelor Level

Ottar L. Osen and Robin T. Bye

Software and Intelligent Control Engineering Laboratory, Department of ICT and Natural Sciences,

Faculty of Information Technology and Electrical Engineering, Norwegian University of Science and Technology

NTNU, Postboks 1517, NO-6025 Ålesund, Norway

Keywords:

Active Learning, Problem-Solving Learning, Assessment, Engineering Pedagogy and Didactics.

Abstract:

This paper reﬂects on a number of observations the authors have made over many years of teaching courses in

electrical and computer engineering bachelor programmes. We suggest various methods and tips for improv-

ing lectures, attendance, group work, and compulsory coursework, and discuss aspects of facilitating active

learning, focussing on simple in-classroom activities and larger problem-based activities such as assignments,

projects, and laboratory work. Moreover, we identify solving real-world problems by means of practical appli-

cation of relevant theory as key to achieving intended learning outcomes. Our observations and reﬂections are

then put into a theoretical context, including students’ approaches of learning, constructive alignment, active

learning, and problem-based versus problem-solving learning. Finally, we present and discuss some recent

results from a student evaluation survey and draw some conclusions.

1 INTRODUCTION

In this paper we reﬂect on various aspects of teach-

ing electrical and computer engineering courses based

on our experiences from about 23 years of teaching

combined (14 and 9 years for the ﬁrst and second

author, respectively) at the Norwegian University of

Science and Technology (NTNU) (formerly Aalesund

University College (AAUC) before 1 January 2016).

We have taught courses both in the computer, au-

tomation, and power systems bachelor programmes

that we offer as well as in our master programmes

in simulation and visualization and product and sys-

tem design. The courses we have taught involve lin-

ear control theory and cybernetics; industrial control

systems, microcontrollers, and instrumentation; arti-

ﬁcial intelligence and intelligent systems; functional

programming; and computer graphics, with aspects

of modelling and simulation embedded in most of

our courses. In line with the role that university col-

leges in Norway have traditionally played, our teach-

ing have always had a practical approach, focussing

on the application of a sound theoretical foundation

to solve real-world problems that our graduates face

as professionals.

In the following, we will reﬂect on our experi-

ences from teaching, focussing mainly on undergrad-

uate courses, and kindly ask the reader to please keep

in mind the following:

• These are our subjective experiences, based on

years of teaching activities, discussions among the

faculty, and student feedback.

• Our experiences are naturally greatly inﬂuenced

by factors such as personalities, education and

work experience, authority, and likability (or lack

of these).

• Our students are mostly young men in their early

twenties from the town of Ålesund and the sur-

rounding region.

• About 50% of our students have background from

vocational school, thus with a tendency to be more

practically than theoretically inclined.

• Our classes have usually had about 20–40 stu-

dents, some as little as 8–12, which is quite differ-

ent from larger classes of 100 or more students.

As such, we are perfectly aware that what we present

in this paper does not generalise to all kinds of teach-

ers, courses, and students. Still, we hope that inter-

ested readers will be able to extract and adopt several

of our ideas and approaches in their own teaching.

Osen, O. and Bye, R.

Reﬂections on Teaching Electrical and Computer Engineering Courses at the Bachelor Level.

DOI: 10.5220/0006359000570068

In Proceedings of the 9th International Conference on Computer Supported Education (CSEDU 2017) - Volume 2, pages 57-68

ISBN: 978-989-758-240-0

1.1 Outline

The remainder of this paper consists of three main

parts. In the ﬁrst part (Section 2), we summarise

a number of observations from our teaching experi-

ences and reﬂect on these. In the second part (Sec-

tion 3), we discuss our ﬁndings in relation to rele-

vant pedagogical literature and theory. In the third

part (Section 4), we include results from a recent stu-

dent evaluation survey that was undertaken in January

2017 by ﬁnal semester engineering students enrolled

in computer, automation, and power systems bache-

lor programmes at our institution. Finally, we make

some concluding remarks (Section 5).

2 OBSERVATIONS AND

REFLECTIONS

2.1 Attendance

Although our study programmes do not enforce

mandatory attendance we believe that in order to be-

come a good engineer it is generally important to

attend classes as much as possible. This of course

demands that the classes we teach must be of sufﬁ-

cient quality and be attractive to students. One way

of improving attendance is to facilitate learning ac-

tivities that complement the traditional lectures and

that are sometimes missing or have limitations in

courses offered online or at more traditional univer-

sities with larger classes and more theory-heavy de-

gree programmes. Such learning activities may in-

clude good individual tutoring and feedback to each

and every student, lectures on topics not covered in

textbooks, laboratory work, group assignments and

projects, all within an active learning environment.

Even though attendance is not mandatory we have

often practised calling the roll before the class starts.

Calling students’ names can be done quite quickly

and does not shorten the time available by any sub-

stantial amount. This practice has several beneﬁts, for

example, fewer students arrive late since they want to

be present when their name is called, and also more

students attend classes. The reason for this is likely

because calling their names seems to make a social

pressure to be present and probably also shows stu-

dents that the teacher care about whether they are

present or not. Indeed, we have experienced stu-

dents that have happened to be away from class due

to a doctor’s appointment send text messages to class-

mates for them to explain to the teacher their friend’s

absence. We interpret this as a willingness from the

students to obey to a “rule” of attendance even if at-

tendance is not mandatory.

We believe this kind of social contracts between

the teacher and the students and between students

themselves can be a useful tool and may be further de-

veloped, since unspoken rules or norms are less sub-

ject to negative pressure or resistance when they are

not formalised (mandatory) and therefore are acted

upon on more of a subconscious level.

2.2 Lectures

There is a common notion that active learning activ-

ities such as solving problems and doing projects are

favourable to the traditional lectures. We have done

some simple tests of how much students remember

directly after a lecture and admittedly been rather dis-

appointed at the results. We believe the inactive and

passive role of the students during a lecture is the rea-

son for this and we welcome methods of activating

the students in the classroom for example by means

of “clickers,” quizzes, competitions, discussions, and

so on. However, there are situations when traditional

lectures must be given, for example when the material

is not covered by textbooks or online video lectures.

In these situations, we have often preferred to use the

blackboard and write by hand. The advantage of this

is that it encourages the students to be active and to

take down the notes themselves simultaneously, since

the students know they have ample time to write down

whatever is being written on the blackboard.

Using slides, on the other hand, often have the ef-

fect that students generally become passive listeners;

they see no point in taking notes since the slides will

usually be available electronically, and often there

will not be enough time to copy down everything.

To illustrate this point, we recap an experiment once

done in class: After showing a slide with three main

bullet points, each with three sub-bullet points (a

fairly standard slide), the bullet points were read out

loud and the students were given plenty of time to

read the slide. Thereafter, the presentation was muted

by showing the students a black slide and then they

were asked to recreate the previous slide. In a class of

about 30 students, nobody was able to do so.

Before teaching a new topic it can be useful to

paint a backdrop for the students and put the topic

into perspective. This usually requires slides, pic-

tures, videos, internet resources, or ﬁgures, diagrams

or charts. However, the content that is presented sim-

ply serves as an introductory preparation for the stu-

dents for storing the knowledge that will be presented

to them afterwards in much more detail. The idea is

that such a short keynote talk will give the students

CSEDU 2017 - 9th International Conference on Computer Supported Education

some mental hooks they can use for storing the de-

tails that follow.

We have also found that students are more moti-

vated and attentive if the lecture is closely connected

to a problem to be solved in an assignment or an ex-

ercise. As a precursor to giving a lecture, an approach

is to ask the students to start working on a prob-

lem and give some individual assistance until at some

stage most of the students realise that they need more

knowledge to solve the problem. When the teacher

then approach the blackboard, the students will be at-

tentive and motivated for learning the theory required

for solving the problem. In contrast, starting a lecture

by saying that the students will need this or that for

their assignment does not give the same effect.

Finally, we have found that it is a good idea to

keep lectures short, or at least break up lectures regu-

larly with active learning activities.

2.3 Student Groups

Project-based learning (see Section 2.5) is an impor-

tant pedagogic tool that usually requires placing stu-

dents together in suitable groups. Experience tells us

that group dynamics can both bring the best or worst

out of a group. Below we discuss our experiences

on various aspects of constructing student groups for

projects.

2.3.1 Size

How large a group should be depends of course on

the estimated amount of work in the project (or as-

signments). For smaller assignments, groups of two

are sufﬁcient, but normally we will aim for groups

of four, and try to avoid groups with odd numbers.

The reasoning behind this is that students working

on a task in pairs are able to communicate efﬁciently

and require both participants in the pair to be active.

In groups of three, we have often observed that one

member is less active than the other two and in the

worst case, the third member becomes a mere ob-

server. Since oral communication only allows for the

ideas of one participant to be shared at any time a

group of two is the most effective. However, a big

drawback with groups of only two students is their

limited capacity if the assignment is big and/or re-

quires competence that may not be held among the

group members. Hence, we generally favour groups

of four. Finally, with four participants it is possible to

make two subgroups that support each other and may

re-arrange themselves depending on the tasks at hand

and the competence within the group.

2.3.2 Selection of Group Members

In general, we favour selecting random groups. There

are several reasons for this. If students are allowed

to make groups by their own choice they will of-

ten assemble groups that follow existing social struc-

tures. As a result, the groups will often become

rather homogeneous and strengthen these existing so-

cial bonds. The upside is that many of these homoge-

neous groups will have little internal friction and will

not require time to socialise since the students already

know each other. The downside is that such homo-

geneous groups may lack the necessary diversity in

competence to solve the problems they are facing.

Furthermore, forming student groups at random

results in more heterogeneous groups and can help

the teaching environment by widening the social net-

works in the class. It forces students to get to know

each other when working on a common challenge and

they therefore become less reluctant to ask questions

in class and to interact.

We have often experienced some resistance from

students when they are told they may not construct

the groups themselves. This is to be expected, after

all, most people are resistant to changes and will feel

more comfortable with people they know. Neverthe-

less, challenging this resistance is important in order

to get optimal results.

Moreover, we can often improve the heterogene-

ity in the groups by not selecting the students 100%

randomly, but instead also take into account their sex

and background. For example, since we usually have

very few female students, we generally prefer to make

sure they are distributed evenly amongst the groups,

unless there are good reasons not to. In a similar vein,

the vast majority of students are native Norwegians,

therefore, we try to distribute the non-natives evenly

among the groups in order to improve integration.

In addition, we often take into consideration that

about half of our students have experience from vo-

cational school. These students often have hands-

on practical experience that can be very valuable in

assignments with a large practical component. By

making sure there is a good mix in the groups, stu-

dents with a more theoretical/academic background

learn practical skills from their fellow students with

a vocational background. Likewise the students with

vocational background improve their methodological

skills by learning from the more theoretical students.

This way of grouping students may seem to re-

quire much work from the lecturer, however, by re-

peatedly pulling two names randomly from each of

two lists of students (one for those who have voca-

tional training and one for those without), we quickly

Reﬂections on Teaching Electrical and Computer Engineering Courses at the Bachelor Level

get a set of possible groups, which then can be rear-

ranged somewhat in order to get a better distribution

of females and non-native Norwegians.

When presenting the groups to the students we do

not mention such ﬁne-tuning and instead emphasise

that the groups have been put together randomly. We

also remind them that working together in groups set

down by others is something they must expect to do

when they start working professionally and that coop-

eration skills will be beneﬁcial for them in their future

work. Finally, we randomly pick a group member to

be the leader of the group. This person’s responsibil-

ity is to make sure the group meets sufﬁciently often,

that everyone contributes, and to report group mal-

functioning to the teacher.

2.4 Compulsory Coursework

From our experience with various approaches, we be-

lieve that compulsory coursework is very often re-

quired in order to make the students work steadily

throughout the semester. We have found that stu-

dents’ performance improved about one grade on av-

erage after making the coursework compulsory in

some courses.

At our institution we use an electronic learn-

ing management system for handing in assignments,

however, we have found it very effective to also ask

the students to show the teacher their work in per-

son, especially on more practical topics, for exam-

ple where the students are required to write computer

programmes or otherwise use computers for their so-

lutions. Much too often we have found that stu-

dents split the work unequally to such an extent that

some students have never had the actual computer

programme or design running on their own comput-

ers. By doing such quick spot checks we force the

students to familiarise themselves with the problem

and have an individually working solution they can

understand and explain even if they have had a lot of

help from fellow students.

When designing coursework, we believe it is good

practice to start with simple questions and subprob-

lems and proceed in a stepwise manner in order to

guide the students’ progress, in other words, making

the assignments seem more like tutorials. There is

a lot to be learnt from a well-formed question and

even good students will not ﬁnd this approach bor-

ing. Making good assignments is of course a lot of

work, but is probably even more important than mak-

ing good lectures.

2.5 Project-based Learning

2.5.1 Project Selection and Ownership

We usually let students choose between a selection

of assignments or projects, and sometimes even en-

courage them to participate in deﬁning the problem, if

possible. The reason for this is that the students seem

to be willing to invest more time and effort into tasks

to which they have ownership. They seem more re-

luctant to “lower the bar” if they have ﬁrst put it high

themselves. In other words, they are willing to suf-

fer more from “self-inﬂicted pain” than from “pain”

given to them by the teacher.

This willingness to invest more time and effort

into activities the students feel ownership to may be

a result of pride but may also be a result of “self-

love.” We believe people in general are less likely to

blame themselves than others since blaming oneself

is very tiresome in the long run. Hence, it is bene-

ﬁcial to avoid giving students opportunity to blame

the teacher’s poor assignment for their own lack of

progress or success. Giving students ownership to the

activity and giving a clear framework for execution

helps in putting the responsibility for success ﬁrmly

on the shoulders of the students themselves.

2.5.2 Project Planning

Project planning is important in order to make the

students aware of time expenditure versus progress.

We prefer to let the students ﬁrst make their plans

themselves before having to submit their plans to the

teacher for approval. The requirements for the plans

are that they should show how the different activities

are spaced out in time; the size of the tasks (dura-

tion); and the responsibility for the tasks. When ap-

proving their plans, we make sure their plans are suf-

ﬁciently detailed and that they have taken into consid-

eration constraints in both time and resources. Ask-

ing the students to make plans forces them to apply a

common engineering approach of breaking the work

down into manageable tasks, which is also important

in order for them to understand the scope of the work

ahead. Moreover, we insist on the responsibility for

each task to be assigned to a single student. In ad-

dition, we usually recommend that one other student

is assigned as a task assistant. This way, there is no

doubt who is responsible for a particular task, while

at the same time, the responsible student has another

student to help out. This will prevent the many dis-

cussions and possible sources for misunderstandings

that can arise when tasks are not completed on time.

Throughout a project, we regularly ask the stu-

dents to update their plans with task completeness

CSEDU 2017 - 9th International Conference on Computer Supported Education

given as a percentage. As a result, the students will

immediately detect any lack of progress and see the

need to take appropriate measures at a time when it is

still possible to inﬂuence the result. In short, we want

the students to panic well ahead of delivery date!

Further down the road, it is usually not neces-

sary for the teacher to comment much on students’

plan updates. Quite often the students will be behind

schedule but it will be visible in their plans and the

need to improve progress will be self-evident. Occa-

sionally, we ask the students to present the updated

plan to the teacher in person in order to “increase

the pressure” and to verify their understanding of the

project status.

2.6 Assessment

2.6.1 Oral and Written Exams

It is well known that many students dread oral exams

out of (a sometimes unjustiﬁed) fear of performing

worse than they think would have in a written exam.

On the other hand, many students may fare better at

oral exams, for example if they have dyslexia or for

other reasons struggle with written communication,

or if the written exam is designed in a poor man-

ner that prevents students from displaying their true

knowledge, competence, and skills. Hence, both writ-

ten and oral exams will be, or at least conceived to be,

disadvantageous to some students and advantageous

to others. Nevertheless, if limited to only these two

means for evaluting students’ performance, a good

mix of oral and written exams can be considered fair

to the students. Still, we would like to point out that

a particular advantage of oral exams over written ex-

ams is that it is possible for the examiner to adjust

the exam questions ad hoc, for example if a student is

nervous. Therefore, a good oral examiner will be able

to both uncover lack of knowledge and skill as well

as providing an opportunity for students to show the

opposite.

2.6.2 Group Exams

One drawback with project assignments is that it is

hard to give individual grades to the students. One

approach to enable individual grades is to add an oral

exam in addition to a written report. By using the re-

port as a starting point, it is possible to at obtain some

variation in grades within the group, if appropriate.

This approach is probably not perfect but it will typi-

cally give a fairer reﬂection of the differences in skills

and knowledge within the group.

We have also experimented with giving oral ex-

ams with the whole group present instead of individ-

ually. The students will sit in alphabetical order, they

are given individual questions one at the time, and

they may not speak out of order. An advantage of

this approach is that the total examination time can be

reduced compared with individual oral exams, since

unanswered questions in a given context can immedi-

ately be passed on to the next student without repeat-

ing it and less time is used for bringing students in and

out of the examination room.

Another important advantage is that the examiner

can more easily compare the students with each other,

whilst at the same time, the students can observe for

themselves who is able to provide the best answers

and they will therefore have a better understanding of

why they deserve the grade they get. We suspect this

has the effect that individual students work harder in

group projects because they are assessed individually

and therefore will have the reward of a fair and better

grade than fellow students who do not put in the same

effort.

2.6.3 Exam Preparation

Nervousness, anxiety, or stress related to exams are

quite common. If students feel secure and good about

themselves and have a feeling of being in control, they

will likely be more prone to deeper learning and typi-

cally perform better at exam. One way of helping stu-

dents to get into this positive state of mind is to reduce

uncertainty about the exam procedure and content, for

example by providing a well-deﬁned curriculum for

the course, run mock exams or practice presentation

skills in class, and provide practical information about

the exam.

Moreover, we have had good experience with giv-

ing the students a long list of possible exam questions

to study before the exam, often provided at the start

of the semester. By making the list long and the ques-

tions rather open we can ensure that if the students are

able to answer most of the questions adequately they

will also have good coverage of the curriculum and

achieved most of the intended learning outcomes and

hence will have better chances of obtaining a good

grade.

Interestingly, we believe that having such a long

list of questions is not of such big help to the stu-

dents as they tend to believe it is. Rather, its main

purpose it to help the students getting into a positive

state of mind before the exam. Indeed, with a well-

deﬁned curriculum and list of intended learning out-

comes and good supporting material such as a course

textbook, students should be able to make such a list

themselves, however, getting the list from the lecturer

removes a lot of uncertainty and stress from the stu-

dents.

Reﬂections on Teaching Electrical and Computer Engineering Courses at the Bachelor Level

Finally, we often offer a course revision workshop

at the end of the semester, where students can obtain

answers to questions that may have accumulated dur-

ing the semester and to topics they ﬁnd difﬁcult.

3 RELATION TO THEORY

In the following, we highlight some literature and

pedagogical and didactical theory relevant to our ob-

servations and reﬂections above.

3.1 Students’ Approaches to Learning

It is well documented that students’ approaches to

learning has a signiﬁcant effect on achieving learning

outcomes (e.g., Gynnild, 2001; Marton, 1981). Many

studies have tried to identify factors that promote deep

learning (e.g., Baeten et al., 2010; Marton and Booth,

1997; Prosser and Trigwell, 1999), that is, learning

associated with understanding, in contrast to surface

learning, which is learning associated with the mem-

orisation of facts and procedures, and with little or

no understanding as a result (Marton, 1981). In be-

tween deep and surface learning, Case and Marshall

(2004) also describe procedural deep and procedural

surface learning as two learning approaches for stu-

dent learning in engineering contexts. In addition to

these learning approaches along an axis of deep and

surface learning, a commonly observed third category

of learning is socalled strategic learning, where stu-

dents aim for good grades with minimal effort, ignor-

ing whether they achieve the intended learning out-

comes or not (Entwistle and Ramsden, 1983, 2015).

Students tend to have different conceptions of

what learning means, and these conceptions can gen-

erally be categorised hierarchically along an axis from

surface learning to deep learning. For example, ac-

cording to Saeljo (1979) and Marton et al. (1993), stu-

dents conceive learning as

1. increasing one’s knowledge

2. memorising and reproducing

3. applying

4. understanding

5. seeing something in a different way

6. changing as a person

Similarly, and speciﬁc to engineering students, Mar-

shall et al. (1999) suggest the following categories of

how students conceive learning:

1. memorising deﬁnitions, equations and procedures

2. applying equations and procedures

3. making sense of physical concepts and procedures

4. seeing phenomena in the world in a new way

5. changing as a person

Higher education institutions obviously have a

duty to graduate highly qualiﬁed candidates and

avoiding surface learning is a means towards this

goal. However, according to Biggs and Tang (2011),

there has been a dramatic change in higher education

worldwide, maybe due to the workplace increasingly

requiring higher education degrees to qualify for jobs,

with many more people enrolling at universities than

before, from a wider diversity of background. This

has resulted in a shift from perhaps more academ-

ically inclined students previously to students who

may have a poorer background both academically,

socioeconomically and perhaps also motivation-wise,

where higher education studies are perhaps conceived

more as a “necessary evil” in order to simply qualify

for a job.

The big variation among students with respect

to background leads to great differences in learning

strategies and approaches to learning and has neces-

sarily had an impact on how higher education is be-

ing taught (Felder and Brent, 2005). At our institu-

tion, this change in students that we enrol has perhaps

been less radical, since we have mainly been con-

cerned with bachelor engineering programmes and

the “elite” students have generally favoured the bigger

universities in Norway.

Therefore, we are perhaps

better equipped with suitable actions to accommodate

this new generation of students. Indeed, despite the

fact that we also have some very talented students

every year who approach their studies with learning

strategies that favour deep learning, we believe many

of the methods we have described previously are very

useful for counteracting students with lesser motiva-

tion and weaker academic backgrounds.

Moreover, it is well known that lack of self-

monitoring and self-regulation will lead to poor aca-

demic results (Lan, 1996; Borkowski and Thorpe,

1994). One must therefore acknowledge the fact that

the learning environment itself is not sufﬁcient to

achieve intended learning outcomes but is also de-

pendent on the students’ individual skill in select-

ing and structuring the material to be learnt (Gyn-

nild et al., 2008). Formative assessment and feed-

back are an important tool to help students become

self-regulated learners (Nicol and Macfarlane-Dick,

2006). Also, the teacher must facilitate learning

strategies that favour deep learning. One method for

doing so consists of the teacher adopting a role as a fa-

cilitator for learning, adopting a role similar to a per-

AAUC was a small university college before merging with

NTNU to become Norway’s biggest university.

CSEDU 2017 - 9th International Conference on Computer Supported Education

sonal trainer at the gym or a coach (Gynnild et al.,

2007).

In Section 2.5, we describe various aspects of

project-based learning and how the teacher can use

several means to facilitate deeper learning. We try to

make the students adopt project ownership, whereby

they become more willing to invest more time and ef-

fort on the tasks they must accomplish. This can help

reducing a strategic learning strategy where students

are not only doing the work to get a desired grade but

because their pride is at stake, they actually want the

project solution to become as good as possible. Like-

wise, for project planning, we require the students to

presents plans that breaks down the work and include

time, size, and responsibility for tasks. By doing so,

the student are effectively self-monitoring and self-

regulating themselves.

3.2 Constructive Alignment

According to Biggs and Tang (2011), constructive

alignment is a teaching strategy where components

such as the teacher, the students, teaching context,

learning activities, and learning outcomes must be

aligned while maintaining the constructivist view that

students learn by doing, commonly know as active

learning, that is, any learning activity that actively in-

volves the students in the learning process (Prince,

2004). Speciﬁcally, when designing a particular

course, one adopt a backward scheme, starting with

the intended learning outcomes (what competence,

skills, and experience students should have upon com-

pletion of the course), then deﬁne assessment tasks

that closely relates to the intended learning outcomes,

and then proceed to choosing teaching methods and

learning activities aligned with the intended learn-

ing outcomes and assessment tasks (Biggs and Tang,

2011).

We have perhaps not adopted a very rigid scheme

based on constructive alignment for our teaching but

it is clear that we emphasise active learning and con-

structivism and we are very careful in our choice of

assignments and projects to ensure that a successful

completion will lead to intended learning outcomes

being achieved. For example, most of our courses in-

volve compulsory coursework that is closely aligned

with intended learning outcomes. By being com-

pulsory and usually with a pass requirement for ac-

cess to the ﬁnal exam, students are forced to com-

plete the assignments in a satisfactory manner and

will achieve some intended learning outcomes while

doing so. Also, our projects are often open-ended,

where many different approaches can lead to success-

ful completion. This is in line with research-based or

problem-based teaching and can be effective against

too rigid implementations of constructive alignment

where too much simpliﬁcation and generalisation can

in fact counteract deep learning and creativity (Ander-

sen, 2010).

3.3 Assessment

A very important aspect of teaching is the choice

of assessment method. For example, in constructive

alignment, many students are mainly concerned with

achieving grades, not learning. These students have

a surface approach to learning, typically aiming for

memorising and reproducing course curriculum, and

essentially, the exam can be said to deﬁne the curricu-

lum (Biggs and Tang, 2011). Therefore, in construc-

tive aligment, one must align the exam, or rather, the

set of components that make up a grade, such as lab-

oratory exercises, assignments, projects, and oral and

written exams, must all be designed in a manner that

ensures that satisfactory completion also means that

intended learning outcomes are achieved. It makes

obvious sense to accept this premise at least to some

extent, after all, who would want to be a passenger of

an airplane where the pilot had only passed a big writ-

ten exam, and not a variety of practical ﬂight tests?

In our own teaching we have adopted similar

means in a lighter manner, where components such as

lab or project activities perhaps have not affected the

the ﬁnal grade directly but at least usually required

students both to show up and to complete the tasks at

a pass grade level before being granted admission to

a ﬁnal exam.

3.4 Active Learning

As should be clear from our observations and reﬂec-

tions of teaching activities, we are proponents of ac-

tive learning. There are several metastudies that show

that active learning in science, technology, engineer-

ing, and mathematics (STEM) indeed has several ad-

vantages. Prince (2004) found comprehensive sup-

port for core elements of active learning, for example

that students being active during a lecture improve

their ability to reproduce the material later and that

they become more motivated and engaged. Likewise,

Schroeder et al. (2007) found that active learning im-

prove students’ performance, as did Freeman et al.

(2014).

Of particular importance are several studies on co-

operative learning (e.g., Foldnes, 2016; Bowen, 2000;

Johnson et al., 1998; Springer et al., 1999). These

studies show that particularly cooperative learning

strategies are effective for deep learning. In our

Reﬂections on Teaching Electrical and Computer Engineering Courses at the Bachelor Level

own teaching, cooperative learning is a core element,

where students often work in groups not only on

projects and large assignments but sometimes also in

smaller exercises or quizzes that with great effect can

be introduced to break up long lectures.

3.5 Problem-based Versus

Problem-solving Learning

Summarising the results of 800 meta-analyses, Hattie

and Goveia (2013) points out the incredible fact that

problem-based learning does not have a positive effect

on achieving intended learning outcomes! Why is this

so? Sotto (2007) suggests that there is a dinstinction

between problem-based and problem-solving learn-

ing. Speciﬁcally, Sotto argues that for learning to

be successful, one must employ well-designed case

studies and avoid problem-based and student-centred

learning. Speciﬁcally, a pitfall in problem-based

learning activities is that the problem at hand is large

(which is not by itself the problem) and there is no

clear guidance towards how to solve it. Students end

up spending too much time on searching the Internet

or studying textbooks even for solving just small parts

of the problem. Instead, Sotto (2007) argues that the

assignments given must be carefully designed in or-

der for the students to quickly be able to practice the

core knowledge and skillset selected by the teacher.

In our own teaching, we have at least tried to ad-

here to some of the suggestions of Sotto (2007), for

example by ﬁrst providing an open-ended problem us-

ing a top-down approach but instead of leaving the

students alone for an eternal chase of information, we

usually interrupt with more information on the black-

board after some time and guide them towards a so-

lution. Also, we sometimes use case studies where

students work through detailed step-by-step exercises,

carefully avoiding the risk of students spending too

much time on any one step. Finally, we would like

to emphasise the importance of immediate feedback,

often easily achieved in lab work and programming

assignments, as found in a pedagogical study on one

of our courses (Schaathun et al., 2015).

4 RESULTS FROM A STUDENT

EVALUATION SURVEY

All students enrolled in their ﬁnal sixth semester in

January 2017 of the bachelor programmes in automa-

tion, power systems, and computer engineering were

asked to complete an anonymous student evaluation

survey online. Out of approximately 70 students, we

received a total of 31 responses, from 16, 3, and 12

automation, power systems, and computer engineer-

ing students, respectively. The students were asked to

indicate to which degree they agreed with the follow-

ing statements, categorising whether they strongly or

partly agreed or disagreed, or were indifferent:

1. I want more traditional lectures.

2. I want more teaching using the blackboard.

3. I want more active learning activities (exercises,

quizzes, discussion, competitions, etc.).

4. I want more ﬂipped classroom and elearning/online

learning.

5. I want more focus on practical application than theory.

6. I want more problem-solving learning activities.

7. I want more laboratory learning activities.

8. Calling the roll makes it more likely that I will turn up

in class.

9. I want more mandatory coursework.

10. I want more/better feedback on my work during the

semester.

11. I want my ﬁnal grades to be fully decided by oral or

written ﬁnal exams.

12. I want my ﬁnal grades to be composed of several parts

(e.g., lab, assignments, project, midsemester test, ﬁnal

exam).

13. I want more digital exams.

14. I want more home exams.

In addition, they were given the opportunity to

elaborate on the statement and any other issues they

wished to raise.

In the following, we discuss answers relevant for

the observations and reﬂections we have made above.

The results are summarised in Table 1, where the

number n of student responses and the corresponding

percentage is given for each statement and response

category.

4.1 Attendance

Only about 10% of the students strongly or partly

agreed that calling the roll would make it more likely

that they would turn up to class (statement 8), whilst

about 20% were indifferent. On the contrary, about

19% partly disagreed and 52% strongly disagreed

with this statement. This result conﬂicts with our ob-

servations that indeed more students do show up to

class if the roll is called, despite attendance not be-

ing mandatory. We speculate that students in their re-

sponses may have wished to emphasise their own free

will and autonomy in choosing whether to turn up to

class. In Section 2.1, we discuss how social contracts

and unspoken rules and norms can emerge in the re-

lation between teacher and students and among the

students themselves, however, these mechanisms are

CSEDU 2017 - 9th International Conference on Computer Supported Education

Table 1: Results from student evaluation survey.

strongly agree partly agree indifferent partly disagree strongly agree

Statement n % n % n % n % n %

1 0 0.0% 3 9.7% 14 45.2% 10 32.3% 4 12.9%

2 1 3.2% 7 22.6% 12 38.7% 9 29.0% 2 6.5%

3 10 32.3% 12 38.7% 5 16.1% 4 12.9% 0 0.0%

4 6 19.4% 9 29.0% 9 29.0% 6 19.4% 1 3.2%

5 13 41.9% 14 45.2% 4 12.9% 0 0.0% 0 0.0%

6 12 38.7% 13 41.9% 6 19.4% 0 0.0% 0 0.0%

7 8 26.7% 14 46.7% 8 26.7% 0 0.0% 0 0.0%

8 2 6.5% 1 3.2% 6 19.4% 6 19.4% 16 51.6%

9 2 6.5% 8 25.8% 10 32.3% 8 25.8% 3 9.7%

10 22 71.0% 5 16.1% 2 6.5% 2 6.5% 0 0.0%

11 5 16.1% 11 35.5% 9 29.0% 5 16.1% 1 3.2%

12 7 22.6% 5 16.1% 8 25.8% 9 29.0% 2 6.5%

13 15 48.4% 9 29.0% 5 16.1% 2 6.5% 0 0.0%

14 2 6.5% 4 12.9% 15 48.4% 3 9.7% 7 22.6%

acted upon more at a subconscious level than manda-

tory rules, and this may explain why the students fail

to agree with the statement, as they may simply not be

sufﬁciently self-aware to know whether they actually

will yield to social pressure for turning up or not.

Another reason for this result is that the effect of

calling the roll may not be as strong as we think it

is. After all, we have only observed the effect across

different cohorts across different semesters, and not

the same cohort during a single semester. Moreover,

we do not have accurate attendance numbers for all

cohorts, thus our observations are more of a perceived

kind than rigid studies. Finally, our impression that

more students turn up to class when calling the roll

can also be due to variation across different cohorts.

4.2 Lectures

Statements 1 and 2 relates to whether students want

more passive learning activities such as traditional

lectures and more teaching using the blackboard, re-

spectively. It is clear from the responses that the

students do not want want more traditional lectures,

with nobody strongly agreeing with the statement,

and only about 10% partly agreeing, 45% being indif-

ferent, and about 45% partly og strongly disagreeing.

With respect to teaching using blackboard, students

are mainly indifferent (about 39%), or partly agreeing

(23%) or disagreeing (29%), with a slight majority

disagreeing overall.

The results are in correspondence with our obser-

vation and reﬂections in Section 2.2. As teachers,

we wish to emphasise active learning activities, yet,

sometimes lectures or blackboard teaching are neces-

sary. The students seem to think that we and the rest

of our colleagues in the three study programmes em-

ploy about the right amount of blackboard teaching

but should reduce the amount of traditional lectures.

4.3 Active Learning

Statements 3 through 7 relates to active learning ac-

tivities and practical application versus theory. It

is very clear from the responses that the students

want more activities that facilitates active learning, for

example, nobody disagrees (partly or strongly) that

they want more focus on practical application than

theory (statement 5), more problem-solving (state-

ment 6), or more lab work (statement 7). Regarding

more ﬂipped classroom and elearning/online learn-

ing (statement 4), only one student strongly disagree,

whereas six students (about 19%), partly disagree.

With respect to more active learning activities in gen-

eral (statement 3), nobody strongly disagrees and only

about 13% partly disagree. Hence, in agreement with

our own views, it seems safe to conclude that most

students want more active learning activities.

4.4 Mandatory Coursework

Students are mainly indifferent (about 32%) to

whether we should employ more mandatory course-

work (statement 9), with 26% partly agreeing and

the same amount of students partly disagreeing. This

result is as expected and matches the student feed-

back we have got over the years. Many students

know that they do not have the necessary motiva-

tion and willpower to do the necessary work unless

Reﬂections on Teaching Electrical and Computer Engineering Courses at the Bachelor Level

they have mandatory coursework, whereas others, and

often academically more skilled students would like

more freedom in their studies.

4.5 Feedback to Students

An overwhelming majority of students (71% and

16% strongly or partly agree, respectively) wants

more/better individual feedback during the semester

(statement 10). This statement was perhaps badly

phrased, as almost noone would ever say no to more

of a given good, e.g., money. A better question would

be whether students were satisﬁed with the amount

and quality of individual feedback they have received

during their studies. Still, this result strongly indicates

that students are not satisﬁed with the current state of

affairs and our department will need to investigate this

issue further.

That students are concerned with not getting

enough individual feedback may also be an indicator

of lack of self-monitoring and self-regulation skills,

which to some extent can be mitigated by facilitating

learning activities where students adopt ownership,

such as projects or lab work.

4.6 Grades and Exams

Statements 11 and 12 relates to whether the ﬁnal

grade of a course should be fully decided by a sin-

gle oral or written exam (statement 11) or be com-

posed of several parts, such as lab work, assignments,

projects, midsemester tests, and ﬁnal exams (state-

ment 12). The majority of students want a single ﬁ-

nal exam to be decisive for their grades (about 16%

strongly agreed, 36% partly agreed, and 29% were in-

different). Interestingly, the majority of students also

want their ﬁnal grades to be composed of several parts

(about 23% strongly agreed, 16% partly agreed, and

26% were indifferent) but with more disagreement

(29% partly disagreed and 7% strongly disagreed)

than for statement 11 (16% partly disagreed and 3%

strongly disagreed).

Historically and currently, we almost exclusively

use a single ﬁnal exam to determine grades but in

many courses we have mandatory coursework that

must be passed for access to the exam. The results

suggest students want both grading approaches and

consequently, we should probably increase the num-

ber of courses where the ﬁnal grade is composed of

several parts.

Regarding digital exams (statement 13) and home

exams (statement 14), a large majority of stu-

dents wants more digital exams (about 48% strongly

agreed, 29% partly agreed, 16% were indifferent,

7% partly disagreed, and nobody strongly disagreed),

whereas the majority are indifferent (48%) or partly

(10%) or strongly disagreed (23%) with wanting to

have more home exams.

Digital exams have just recently started to take

places in only a few of our courses but will increase

in the future, partly because of administrative pressure

but also because of various advantages, especially in

some courses where this examination kind is suitable,

such as programming-related courses.

Home exams have hardly ever been offered our

courses, thus it is somewhat surprising to observe stu-

dent resistance against a kind of examination that they

have never experienced (at least not during their stud-

ies). There is currently no plan to begin to offer home

exams in our courses as far as we know.

5 CONCLUDING REMARKS

In this paper, we have summarised some of the ob-

servations and reﬂections we have made after many

years of teaching courses in computer and electri-

cal engineering bachelor programmes. We have put

the observations and reﬂections into theoretical con-

text, and ﬁnally, we have provided some insight into

what current students think about the learning activ-

ities that we provide, and how we examine students,

through a ﬁnal semester student evaluation survey. In

line with the most up to date literature, we empha-

sise that higher education of today is still in need of

a shift away from passive learning activities such as

traditional lectures towards active learning activities

in the classroom, with more problem-solving and lab-

oratory work, whilst focussing on practical real-world

application with a sound theoretical foundation. The

survey indicates that our students tend to agree with

this view.

Whilst many students want a single ﬁnal exam

grade, many students also want their grades to be

composed of several parts. The latter is a viewpoint

that we share and it is also a key component of con-

structive alignment, keeping in mind that many stu-

dents are more concerned with exam grades than with

what they actually learn.

We have just recently begun to use digital exams,

only for a few of our courses. A large majority of stu-

dents appreciate this new trend and want more digital

exams, a change that is likely to happen the next few

years.

Regarding future work, we would like to do some

more rigid studies on the discrepancies between the

survey results and the reﬂections on various teaching

methods discussed in this paper. Such studies should

CSEDU 2017 - 9th International Conference on Computer Supported Education

try to establish more ﬁrmly whether the perceived ef-

fects of the proposed methods are real and advanta-

geous. We also need to collect more and better student

evaluation data, as well as continue to improve and fa-

cilitate an active learning environment. Moreover, we

would like to formalise our teaching methods slightly,

and possibly adopt ﬂipped classroom in several of our

bachelor courses similarly to what we have done for a

master’s course on artiﬁcial intelligence (Bye, 2017).

Finally, we wish to underline that only a fraction

of all the interesting aspects of teaching computer

and electrical engineering courses at the undergradu-

ate level have been covered in this paper, and that our

observations and reﬂections are necessarily subjective

in nature. Nevertheless, we hope that the interested

reader is able to make valuable use of at least some of

the methods we suggest in their own teaching.

ACKNOWLEDGEMENTS

The Software and Intelligent Control (SoftICE) Labo-

ratory is grateful for the ﬁnancial support given by the

Study Committee at NTNU in Ålesund through the

project Research-based and Innovation-driven Learn-

ing (FILA), grant no. 70440500.

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