Formative e-Assessment in Engineering Education

Odysseus Tsakiridis

and Panos Photopoulos

Department of Electrical and Electronics Engineering, University of West Attica,

250 Thivon & P. Ralli Str., Athens, Greece

Keywords: Learning Management System, Engineering Education, Formative e-Assessment.

Abstract: This paper presents a pedagogical practice introduced to second-year undergraduate Electrical and Electronic

Engineering students to enhance learning and understanding during the classes. The practice consisted of four

formative, objective-type e-assessments taken in two months. Each assessment followed a two-week teaching

period. During the e-tests, the students used their notes and worked in groups or independently. Each test

included a small number of problems in Electronics uploaded at the course's web page. The assessments were

not competitive, and the students were allowed to discuss the solutions with the tutor during the problem-

solving session. After the fourth test, the students evaluated the practice by answering a survey. The responses

showed high satisfaction with the e-assessment, student retention during classes and active participation. The

e-assessment increased students' engagement through interactive learning in a non-competitive environment,

followed by a moderate improvement in the final examinations' grades. This paper highlights the opportunity

to mobilise students' active participation in the lectures and bring closer teaching, learning and assessment

with the help of the Learning Management System (LMS).

1 INTRODUCTION

Tutors and educational institutions are concerned

with student performance manifested in grade

distribution, completion of the studies and student

retention. Student engagement is a complex construct

that makes student success more probable. It accounts

for students' connectedness to the institution, and it is

related to self-regulation of learning. Engagement and

self-regulation in learning are considered to

positively impact student performance and retention

(Kahu & Nelson, 2018; Gourlay et al., 2021;

Carmona-Halty et al., 2021). Fine-tuning of the

student-institution interface increases feelings of

acceptance, support and belonging and positively

affects engagement. However, engagement is not the

only construct linked to student performance. Interest

and caring for the students have also been proposed

to drive student success. Interest increases student

motivation for learning and positively impacts

academic performance (Harackiewicz, Smith &

Priniski 2016). Caring for the students mobilises their

willingness to learn and enhances participation in

https://orcid.org/0000-0002-6014-1783

https://orcid.org/0000-0001-7944-666X

classroom activities (Miller & Mills, 2019; Miller

2020). If student success is the desired outcome,

engagement, care for the students, and interest are

equally probable antecedents, although the first has

attracted the most attention. However, student

engagement requires a more holistic intervention at

the level of the institution while cultivating a friendly,

supportive and inclusive learning environment lies in

the hands of the tutor. Classroom-based interactive

activities have a more local character, facilitating co-

regulated learning. Formative e-assessment asks the

students 'to do' rather than passively listening during

classes.

Recent literature reviews conclude that formative

e-assessment results in co-regulation of learning and

motivation (Andrade et al., 2021). However, it is still

not clear whether self-regulation (Allal, 2019) or co-

regulation (Yang, 2019) is the outcome of this

classroom student-centred activity.

Besides, e-assessments provide feedback to

instructors and students (Kearney, & Perkins, 2014;

Farrag, 2020; Andrade et al., 2021), which is

particularly useful in evaluating the quality of

teaching and learning (Black & Wiliam, 2006).

562

Tsakiridis, O. and Photopoulos, P.

Formative e-Assessment in Engineering Education.

DOI: 10.5220/0011116800003182

In Proceedings of the 14th International Conference on Computer Supported Education (CSEDU 2022) - Volume 2, pages 562-569

ISBN: 978-989-758-562-3; ISSN: 2184-5026

Formative e-assessment gauges students'

development and has been characterised as

"assessment for learning" (Biggs, 1999).

Wiliam and Thompson (2007), inspired by

strategic planning, linked formative assessment to the

following questions: "Where am I now in terms of

learning?", "where I must go?" and "what needs to be

done to get there?". They proposed that formative

assessment consists of five key strategies resulting

from the above questions: 1. Clarifying and sharing

learning intentions and criteria for success; 2.

Engineering effective classroom discussions and

other learning tasks that elicit evidence of student

understanding; 3. Providing feedback that moves

learners forward; 4. Activating students as

instructional resources for one another; and 5.

Activating students as the owners of their learning.

Feedback is helpful to the student, but it does not

necessarily lead to good results. Only the students

who use feedback to self-regulate their learning

(Perrenoud 1998, Black & Wiliam 2009) or proceed

to corrective activities, e.g. revision (Chaktsiris &

Southworth 2019), are more likely to succeed. The

spatial and temporal distance between feedback and

the corrective action requires the student to have an

adequate level of interest, engagement, or self-

motivation to invest time and effort in more studying.

Giving time to the students to test their understanding,

identify misconceptions and learn during the classes

can enhance their self-efficacy, cognitive engagement

and self-regulation. The skill of self-regulation is

acquired through social interactions, which enhance

students' self-efficacy (McInerney & King, 2018).

Making the formative e-assessment a non-

competitive classroom activity allows instant

feedback and correction during the assessment. This

strategy is attractive even to the students who are not

high performers.

Relative to the five critical strategies suggested by

Wiliam and Thompson (2007), our conception of the

formative e-assessment suggests that:

1. It creates an environment that resembles

summative assessment but is less stressful and more

supportive. It supports the students to realise the

learning objectives of the course through

collaborative problem-solving.

2. It allows the students to receive support from

the tutor and cooperate with peers to enhance rather

than merely evaluate their understanding.

3. Students do not receive feedback after the

assessment; it is available as they try alternative

problem-solving strategies. It provides feedback for

understanding.

4. It removes competition between students or

groups of students. The students have a common

objective: to understand.

5. Students use their class notes and cooperate

with peers. They start thinking of teaching, learning

and assessment as a whole.

The research questions of this publications are:

a) Which are the students' attitudes towards the

studies and the proposed practice?

b) To what extent do the students consider the

particular practice appropriate for other courses?

2 THE PEDAGOGICAL

PRACTICE

Analogue Electronics II is a second-year course

delivered during two 3-hour sessions per week. The

course introduces the students to linear and high-

frequency amplifier models, multistage amplifiers,

AC and DC coupling of amplifiers, op-amps and

advanced op-amp applications, power amplifiers,

thermal analysis, distortion and noise, feedback

topologies, oscillation criteria and multistage

amplifiers' feedback analysis. It includes circuit

analysis and design using circuit simulation software.

In October 2021, a formative e-assessment

practice was introduced. The proposed practice was

designed to bring closer teaching, learning and

assessment trigger dialogue and cooperation between

the students and between the students and the tutor. It

was considered an opportunity to increase students'

interest in the lectures, ignite active participation and

make learning and understanding a classroom

activity. There was no restriction to the resources

used, allowing the students to work in groups and

consult the tutor. Giving time to the students to

experiment during the classes would make them

realise that learning is highly valued. The tutor's

presence and support during the formative e-

assessment demonstrated caring for their

understanding (Miller & Mills, 2019; Miller 2020). It

also showed the students that learning and

understanding are not tasks of the lonely learner that

take place a few days before the exams, but part of

teaching and the tutor's interest. The proposed

practice aimed to improve student retention, motivate

them to follow the classes actively and increase

students' success in the final exams.

Every second week the students dedicated one

hour to the practice. At the end of the fourth week, the

tutor presented the project outline and explained its

objectives. Each e-test consisted of three to four

Formative e-Assessment in Engineering Education

563

problems presented in multiple-choice, multiple

correct or right-wrong questions. Before each e-

assessment, the problems were uploaded to the

course's LMS in the form of objective questions. The

students accessed the problems using their mobile

phones and submitted the number-answers

electronically. Answering the questions demanded

calculations, circuit drawing and extended thinking.

Marking was done automatically, and the students

received feedback immediately after the e-

assessment.

Problem-solving is central in engineering

education. Problems in electronics involve circuits,

power sources, conventions regarding the currents

and the potential, etc. A circuit is not merely a

drawing of interconnected devices but involves

visualising imagery, extended thinking, and other

non-routine activities. The topology of a circuit

intervenes with the "canonical object frames" (Chi,

Feltovich, Glaser, 1981) of the various devices and

the current and voltage interrelations. Overcoming

misconceptions on physical quantities and using

correct approximations is necessary for successful

problem-solving in engineering studies. Good

knowledge of theory alone is not enough to solve

problems, and problem-solving is an effective way

for students to exercise their understanding of

electronics (Photopoulos, Triantis, 2022).

The students were allowed to work in groups or

individually. They used their class notes and asked for

help from the tutor. However, the students could

consult the tutor after completing a solution. The

problem solutions became available to the students

immediately after the e-assessment on the course's

web page. The first e-assessment was introduced at

the end of the sixth week. At the end of the semester,

the students evaluated the practice using a

questionnaire. Apart from demographic information,

the questionnaire collected information in two

directions. The first had to do with students' attitudes

concerning their studies, namely what they do during

the classes, how they learn, how much effort they put

into studying independently, and years to complete

duration. The second was on the evaluation of the

applied practice.

3 COLLECTION OF DATA

During the 12th week of the course, the participants

were invited to evaluate the pedagogical practice. The

participation was voluntary, the responses were

anonymous, and consent was obtained before the 56

participants (50 male and six female) entered the

research. One of the authors created the questionnaire

hosted on the Google platform. There were no

incentives for completing the questionnaire. The

items were written in Greek, and the link to the survey

was communicated to the participants via e-mail. The

demographic questions collected information on age,

gender and year of enrolment. Half of the participants

were in the second year of their studies. In the first

section of the questionnaire, the students gave a

snapshot of themselves as learners. For example, the

item ‘As far as my studies are concerned, I am a self-

disciplined person’ recorded students’ beliefs on self-

control. Other items asked the students what they do

when following lectures, (take notes, focus on what is

said or focus on the blackboard), hours of home study,

and whether they mostly learn studying at home or

during the lectures.

The second section of the questionnaire recorded

students’ experience of e-assessment (Table 1). The

responses were on a Likert-type scale ranging from 1

= ‘I totally disagree’ to 10 = ‘I totally agree’ (Table

I). The questionnaire included a free text answer on

the evaluation of the practice. Ninety per cent of the

respondents considered the e-assessment “a positive

experience.”

Table 1: Questionnaire scoring.

Item

Mean SD

The e-assessment allowed me

to understan

etter.

8,14 2,28

The e-assessment helped me

to clarify aspects I had not

understood.

8,05 1,85

The e-assessment made me

pay more attention during the

lectures.

8,32 1.85

During the e-assessment, I

worke

roductively.

8,18 1.61

The e-assessment motivated

me to learn.

7.68 2,12

The e-assessment showed me

that the tutor cares for our

learning.

8,68 2.13

The e-assessments were

carefull

ared.

8,54 1,57

The e-assessment took place

at the ri

ht moment.

8,32 2,02

The fact that we were all

working together created a

sense of "communit

7,89 2,10

I would like to have e-

assessments in othe

courses.

8,18 2,33

If there are e-assessments in

other courses, I will attend

more lectures.

8,21 2,01

CSEDU 2022 - 14th International Conference on Computer Supported Education

564

4 RESULTS

The first section of the questionnaire recorded

students' attitudes regarding their studies. The item

'As far as my studies are concerned, I am a self-

disciplined person' recorded students' beliefs on self-

control. The average score was 6.4 out of 10

(S.D.=2.2). The students also reported a high degree

of self-determination 'When I set a goal in my studies,

nothing distracts me from achieving it' (Mean=7.4,

S.D=2.0). The quantitative data showed that the

majority (64%) of the students consider that most of

their learning happens during the lectures. Only 57%

of the respondents take notes during the classes, 16%

focus on the blackboard, and the rest 27% just listen.

Only 36% replied that they mostly learn "studying at

home."

A Chi-squared test examined whether there was

an association between what the students do during

the classes, i.e., take notes, look or listen and how

they learn, i.e., in the classroom or studying at home.

The result (χ

(2,56) =1.86, p>.05) showed no

statistically significant association. A high percentage

of the students (43%) follow the lectures rather

passively, and the majority of them (64%) expect to

learn during the classes.

Students reported on average 8.2 (S.D.=4,5) of

home-study hours per week and an expected average

duration of studies equal to 6.4 years (S.D.=2,2) when

the degree duration is five years. We divided the

respondents into two groups depending on the

expected years of graduation. The students of the first

group expected to get their degree in 5 or 6 years and

the second group in 7 or 8 or more than eight years.

The students who 'mostly learn studying at home'

reported an average of 10.7 hours (S.D.=4,6, N=20)

of study per week, while the students who 'mostly

learn during lectures' reported 6.9 hours (S.D.=3.8,

n=36). The 2X2 Chi-square test showed a significant

association between the categorical variables

(1,56)=7.45, p=.006<.05 indicates that the mean

study hours difference is not a sampling artifact. We

identified a weak association between the 'hours of

study category' and the self-control over the studies

variable χ

(1,56)=4.83, p=.028<.05. Therefore,

studying harder is associated with the perception of

higher self-control.

We performed a Chi-squared test to examine the

association between the "duration of studies" and

students' learning habits, i.e., whether they learn by

studying at home or during classes. We concluded

that there is no significant association between the

two variables (χ

(1,56)=0.51, p>.05). Similarly, there

was no significant association between the expected

duration of the studies and what the students do

during classes, i.e., whether they are note-takers,

listeners, or focus at the board (χ

(2,56)=1.54, p>.05).

We divided the respondents into two groups

depending on the expected years of graduation. The

first group of students declared that they expected to

get their degree in 5 (the minimum duration of

studies) or six years, while the second group of

students expected to obtain their degree in 7 or 8 or

more than eight years. Sixty-six percent (66%) of the

respondents expect to receive their degree in 5 or 6

years, and the rest 34% in more than six years. Higher

self-control over their studies was weakly associated

with expectations of faster graduation χ

(1,56)=4.37,

p=.037<.05. Finally, higher self-determination over

the studies was associated with fewer years to

graduation χ

(1,56)=5.39, p=.02<.05.

To explore the factor structure of the second

section of the questionnaire, an exploratory factor

analysis with oblique rotation (Direct Oblim) was

performed. The Kaiser-Mayer-Olkin measure of

sampling adequacy was found equal to .89, above the

recommended value of .6, indicating that the

variables were adequately correlated for factor

analysis. This result was verified by Barlett's test of

sphericity, which was found to be significant

(56)=472 p<.001. The communalities were all

greater than .6, confirming the shared variance

between the items. Kaiser's criterion for eigenvalues

greater than 1 yielded a two-factor structure. The first

factor labeled "attitudes" included eight items (items

1 to 8 in Table I) and explained 63% of the variance.

The second labeled 'prospects of the proposed

practice' (items 9 to 11 in Table I) explained 11% of

the variance. The correlation between the two factors

was 55%. Cronbach's alpha for the 'attitudes' factor

was .91, and for 'prospects of the proposed practice '

.80 indicating the internal consistency of the two

subscales.

The Shapiro–Wilk test of normality showed that

the compound variables' attitude' and 'prospects of the

proposed practice' do not follow the normal

distribution. Kruskal-Wallis tests showed no

significant association between the scores of the two

factors and the various categorical variables.

Therefore, no particular subgroup is differentiated

regarding the two compound variables.

5 DISCUSSION

This section discusses the research questions of the

present study, namely: a) Which are the students'

attitudes towards the studies and the proposed

Formative e-Assessment in Engineering Education

565

practice? b) To what extent do the students consider

the particular practice appropriate for other courses?

5.1 Student’s Attitudes

The majority of the students (90%) considered the e-

assessment a positive experience. They gave high

scores to all the items examining their attitudes

towards the new practice. Their positive attitude was

also profound in the free-text answers they gave. One

can explain the enthusiasm considering that the new

practice gave purpose to class participation and

directed students' effort towards more effective

learning.

The survey showed that only 57% of the

respondents take notes during the lectures. It appears

that students hope that being present during the

lectures will result in learning. They spend hours in

amphitheatres, considering that by doing so, they

fulfil their academic duties. Their answers indicate

that passive learning is not uncommon among the

respondents. Passive learning relies on the false belief

that receiving information during a lecture will

somehow increase the individual's knowledge and

abilities to perform specific tasks. Many students

adopt a passive stance during the lectures, which does

not result in learning (Chi & Wylie 2014). The

students do not activate their past knowledge for

making comparisons or searching for its relation to

the information they receive. Sooner or later, they

realise that they do not learn and stop going to the

lectures.

Moreover, 64% of the participants believe or

anticipate learning during the lectures. Putting the

numbers together shows that disappointment is just

around the corner. The absence of association

between "studying hours", "classroom behaviour",

and "studying at home vs. following the lectures"

indicate that many students do not design a strategy

to learn effectively. For many respondents, following

a lecture is not part of an organised learning process

and has a ritualistic character. Overall, the data show

that the students are optimistic regarding the length of

the studies. However, the students who report a

shorter duration of studies do not study more than the

rest of the students. Although one would anticipate

that those students who expect to complete their

studies sooner do something extra for that, we found

no association between the "expected duration of the

studies" and the "studying at home" or the "classroom

behaviour" variable. It appears that the students

embraced e-assessment as an educational practice

because they realised that it guided more effective

learning, a question they had not considered before.

Moreover, it was a practice completed in the

classroom with the supervision and support of the

tutor and it required no extra effort at home.

Learning requires the cognitive engagement of

the learner in meaningful activities (Bonwell &

Eison, 199; Kahu & Nelson, 2018). The survey results

show that the students considered the proposed

intervention as a meaningful learning activity.

Emotional engagement centres on the positive or

negative reactions of the student towards the tutor, the

classmates, and it affects learning (Chi & Wylie

2014). Items 4 to 7 (Table 1) indicate that the students

attained higher emotional engagement during the e-

assessment. Feelings of high self-control or self-

determination over the studies were associated with

faster graduation. However, there was no association

between these variables and the hours of study at

home.

Overall the students reported a positive attitude

towards the e-assessment reporting in all the items

scores higher than 7.5 on a 10 points scale. The

respondents expressed the highest agreement (lowest

standard deviation) to items 2,3, and 4, i.e.

"understanding during the e-assessment", "paying

attention during the lectures because of the e-

assessment", and "working productively during the e-

assessment". Item 6 was the item with the highest

score "the e-exams showed that the tutor cares for our

learning," indicating that in particular cultural

contexts, the tutor's role is indispensable. The

assessment allowed the students to apply theories and

models to solve problems in a supportive

environment. They increased their understanding of

the taught material (Items 1 & 2 in Table I).

Extensive focus on cognitive gains has been

criticised for reflecting lower cognitive development.

Solving real-life engineering problems is a suitable

way for higher-level cognitive development. While

learning to apply models in solving standard textbook

problems in electronics may draw criticisms as rote

learning, good knowledge of them is an antecedent to

real-life engineering problems, which require more

complex decisions. Therefore, achieving a high level

of theoretical mastery is a vital outcome independent

of the targeted cognition level (Say, Visentin,

Cummings, Carr, King, 2022).

Students' satisfaction with the pedagogical

practice improved intrinsic motivation and resulted in

more meaningful class participation (Say, Visentin et

al., 2022). The positive outcomes of students'

satisfaction affected positively their behaviours

manifested in high class attendance, retention to the

e-assessment practice and student-student

cooperation (Hughes et al. 2020). Other outcomes

CSEDU 2022 - 14th International Conference on Computer Supported Education

566

were "more attention during the lectures", 'motivation

to learn", "work productively", and "feelings of

community".

The e-assessment affected the way students attend

the lectures (Item 3). The lecture was no more a

timetable duty but the means to perform well during

the e-assessment. Groupwork presumably energised

the group dynamics, giving a learning community

feeling (Item 9). The e-assessments occurred in a non-

competitive environment where the students shared

ideas with their peers and the tutor. They reconsidered

what they already knew and related past to present

knowledge. Presumably for many of the students, it

was an exciting experience to move from passive to

interactive learning. Although beneficial to the

student, active learning assumes that students are

patient enough to work on their own. The interactive

mode places the learner within a social context.

Learning is not a personal activity, but it results from

interaction with the teacher and fellow students.

Within a group of peers, students learn through

questioning, exchanging understandings, elaborating

and challenging ideas (Molin et al., 2021).

The e-assessment introduced the students to a new

environment where learning and understanding

became the centre of the class activities (Items 6,7 &

8). This experience is in contrast with teacher-

oriented classes. In a student-centred environment,

learning results from what the students do. The tutor

designs the learning activities and allows time for the

students to rethink what has been taught, generate

questions and identify difficulties that challenge their

understanding. Student-student interaction flourishes

in project-based (Čavić et al. 2022) or problem-

solving classes (Hmelo-Silver, 2004).

Hsiao et al. (2022) found that the students who

exhibited interactive, constructive, and active

engagement behaviours are primarily found in

student-centred learning environments, while passive

engagement dominates in tutor-oriented classes. The

e-assessments comprised a series of learning tasks to

direct students towards desired learning goals,

challenging their understanding and eliciting

dialogue and argumentation. The learning activities

(Chi & Wylie 2014) serve and reproduce the learning

environment and influence how students engage with

them. Problem-solving is a good activity for this

purpose. Asking the students to plug a few numbers

in an equation and make calculations serves a tutor-

oriented environment, while problem-solving in

groups promotes student-centred education.

5.2 Prospects of the Proposed Practice

The second composite variable, which resulted from

the factor analysis "prospects of the proposed

practice," explains 11% of the total variance.

Seventy-one per cent (71%) of the respondents scored

higher than 7 for the items "I would like to have e-

exams in other courses" and "if there are e-exams in

other courses, I will attend more lectures". As one

student noticed and the free text question, "it would

be nice if there was e-assessment in other courses. It

motivates me to pay attention during the classes.

Learning becomes easier and classes more useful."

The LMS added formality and flexibility to the e-

assessment. It offered a systematic way to monitor

student participation and performance. It provided a

well-prepared framework that encouraged the

students to work on activities aligned to the learning

objectives. Apart from optimistic accounts of a total

transformation of education using LMSs, the practice

provided evidence of effective use of technology to

enhance student motivation, participation, retention

in a traditional campus-based setting (Coates, 2007).

The survey results showed that the e-assessment was

an opportunity for the students to consider

metacognition issues concerning class participation

and learning strategies.

The survey findings indicate that the students

valued the assessment because it guided their

learning. It responded to their beliefs and

expectations that the classroom must be the place to

learn. It assured them that the tutor cares for their

learning and supports their endeavour, affecting

positively emotional engagement. They realised that

they worked productively during the e-assessment.

The LMS allowed flexibility in assessment formats

while the proposed practice increased their interest in

the lectures and created a learning community.

6 CONCLUSIONS

This study examined students' attitudes of a

pedagogical practice introduced in a second-year

course in Electronics. The purpose of this

intervention was to bring closer lecturing and

assessment with the help of technology. The findings

show that the students consider that the proposed

practice motivated them to engage in more active

class participation, student retention, and improved

learning and understanding. We explain the high

acceptance of the practice because it guided the

students to take ownership of their learning in a

supportive, non-competitive environment.

Formative e-Assessment in Engineering Education

567

The findings of this research shows there is a gap

between students' behaviour and the demands of

University education. The students, especially those

of the first years, find themselves in a new situation

where they do not know how to navigate. Half of the

students attend the classes without making notes;

however, most anticipate learning during the classes

and spend a limited amount of hours studying at

home. The proposed pedagogical practice organised

the active participation of the students and helped

them feel productive and members of a learning

community. It appears that such initiatives are

necessary in order to make class attendance

meaningful and learning more likely to happen.

Despite the students' positive views, the

proposed practice had only a marginally positive

impact on students' final examination grades.

Seventy-one per cent of the student who participated

in the practice obtained a pass mark in the final

examination (Average=5.4 S.D.=1.9) compared to

65% for the rest of the students (Average=4.9

S.D.=2.2). The percentage of the high achievers, i.e.

score greater than 7.5/10, was equal to 13 per cent in

the first group and only 2% in the second. However,

this may be because the more industrious students

participated in the pedagogical practice.

Although the proposed practice did not

significantly affect student performance, it

highlighted the gap between students' attitudes and

the demands of university education. Further research

is needed to identify similar practices, which will take

into count this usually forgotten gap and mobilise the

students to become more active learners.

ACKNOWLEDGEMENTS

The authors are thankful to the University of West

Attica for funding the publication of this article.

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