The Impact of Live Polling Quizzes on Student Engagement and

Performance in Computer Science Lectures: A Post-COVID19 Study

Xingyu Zhao

WMG, University of Warwick, Coventry, U.K.

Department of Computer Science, University of Liverpool, Liverpool, U.K.

Keywords:

Active Learning, Live Polling Quiz, Formative Assessment, Classroom Interactivity, Post COVID19

Education, Real-Time Feedback, Survey Analysis in Education, Behavioural Shift in Learning.

Abstract:

Before COVID19, live polling and real-time feedback tools gained popularity in higher education for enhanc-

ing student engagement, boosting attention, participation, and understanding of course materials. However,

recent changes in learning behaviours due to the pandemic necessitate a reevaluation of these active learn-

ing technologies. In this context, our study focuses on the Computer Science (CS) domain, investigating the

impact of Live Polling Quizzes (LPQs) in undergraduate CS lectures. These quizzes comprise fact-based,

formally deﬁned questions with clear answers, aiming to enhance engagement, learning outcomes, and overall

perceptions of the course module. A survey was conducted among 70 undergraduate CS students, attending

CS modules with and without LPQs. The results revealed that, while LPQs contribute to lecture attendance,

additional factors likely play a larger role in attendance rates. Students generally ﬁnd LPQs beneﬁcial for

understanding content, maintaining attention, and fostering motivation, but also viewing them as essential for

re-establishing peer and instructor connections post-pandemic. Students prefer a balanced LPQ frequency and

clear, accessible instructions, reﬂecting a reliance on digital tools and self-paced engagement habits developed

during remote learning.

1 INTRODUCTION

Before the COVID19, live polling and real-time feed-

back tools were popular in higher education class-

rooms as a way to boost student engagement and

performance in learning (Lim, 2017; Serrano et al.,

2019; Voelkel and Bennett, 2014; Lantz and Stawiski,

2014; DeSouza and Fleming, 2003; Salas-Morera

et al., 2012; Hennig et al., 2019). However, state-

of-the-art research works on the impact of using live

polling systems in in-person lectures were mostly per-

formed based on data collected before the COVID19.

Arguably, students’ learning behaviours may have

changed after the pandemic, following nearly 3 years

without in-person teaching (Rapanta et al., 2021).

The shift to remote learning during COVID19 may

have already altered student engagement and expec-

tations (Cicha et al., 2021). For instance, changes

and new trends regarding the learning environment

are identiﬁed in (Al Ansi and Al-Ansi, 2020), the

new engagement behaviours in hybrid-classrooms is

https://orcid.org/0000-0002-3474-349X

discussed in (Hjersman et al., 2022), and technology

used in blended learning will likely play a critical role

(Imran et al., 2023). In this regard, there is a need

to re-examine student perceptions of active learning

technologies, like live polling and real-time feedback

tools, in light of these changes (Phelps and Moro,

2022; Reimers, 2021), which motivates this work.

Focusing on the Computer Science (CS) domain,

we have undertaken a survey-based investigation to

reevaluate the effects of integrating Live Polling

Quizzes (LPQs) into undergraduate (UG) CS lectures,

where the questions are all based on factual infor-

mation and are formally deﬁned, having clear an-

swers, as opposed to open-ended or opinion-based

questions that lack deﬁnitive answers. Our study re-

volves around several research questions that delve

into aspects such as student engagement, learning out-

comes, ideal frequency and usability, as well as poten-

tial correlations with overall perceptions of the course

module. More speciﬁcally, a survey of 14 questions

(12 multiple choices with Likert scale answers and 2

ﬁll-in-the-blank questions) was distributed to 70 UG

students who have been attending UG CS modules

Zhao, X.

The Impact of Live Polling Quizzes on Student Engagement and Performance in Computer Science Lectures: A Post-COVID19 Study.

DOI: 10.5220/0013218700003932

Paper published under CC license (CC BY-NC-ND 4.0)

In Proceedings of the 17th International Conference on Computer Supported Education (CSEDU 2025) - Volume 1, pages 291-298

ISBN: 978-989-758-746-7; ISSN: 2184-5026

291

with and without using LPQs. 30 responses (in which

28 are valid) were collected and analysed both quan-

titatively and qualitatively. Finally, the threats to va-

lidity are discussed.

The new data shows some insights as follows:

i) Although LPQs may have contributed to higher

attendance, they alone do not completely account for

the higher lecture attendance rates. Other factors may

have contributed more than LPQs.

ii) LPQs were broadly viewed as beneﬁcial for

comprehending lecture content, effective at keeping

students’ attention, motivation and participation.

iii) Post-pandemic, students view LPQs as critical

for rebuilding social connections with peers and in-

structors, ﬁlling a gap left by remote learning. LPQs

help students readjust to live, in-person engagement

and sustained focus, challenging the passive habits

developed during remote, self-paced learning.

iv) Students after COVID19 prioritize clear, ac-

cessible instructions and intuitive technology inter-

faces, reﬂecting their reliance on digital tools during

remote learning.

v) Students prefer a balanced LPQ frequency,

ﬁnding overly frequent quizzes disruptive rather than

engaging—likely inﬂuenced by their autonomy in re-

mote learning during the pandemic.

2 METHOD

Aim. The aim of this study is to assess student per-

ceptions and self-reported behaviours related to the

use of LPQs during CS lectures. Speciﬁcally, the

study seeks to understand if the inclusion of LPQs in-

creases student motivation, engagement, and sense of

understanding and connection in the classroom. Ad-

ditionally, we aim to examine if attendance and par-

ticipation in lectures with LPQs is associated with

students reporting more positive beneﬁts compared to

traditional lectures without these interactive features.

Context. The University of Liverpool (for double-

blind review) is a public research university located in

Liverpool, UK. It is a member of the Russell Group

of leading research-intensive universities in the UK.

Students in their third year of an UG CS programme

at the University of Liverpool are typically working

towards a Bachelor of Science (BSc) degree in CS.

The programme provides students with core computer

science knowledge and skills such as programming,

algorithms, data structures, databases, operating sys-

tems, and more. In their third year, students take ad-

vanced courses like formal methods, machine learn-

ing, and often work on a ﬁnal year project where they

apply what they’ve learned to develop a computing

system or conduct research. The programme prepares

students for careers in software engineering, data sci-

ence, and other technology ﬁelds upon graduation.

Design. A survey with 14 questions (12 multiple-

choice questions and 2 ﬁll-in-the-blank questions),

about 10 minutes in length, was designed to be com-

pleted online in the CANVAS web-based teaching

management system. It was distributed, via links in

emails and notiﬁcations from CANVAS, to the 70 CS

UG students. The student may answer those questions

anonymously and without any time limit in a three

months time window after the mid-term.

Sample. The survey was distributed to a cohort of

70 ﬁnal year CS UG students in my own module, in

which there are 3 lectures per week for 12 weeks. The

general teaching practice around LPQs is shown in

Figure 1. Before each lecture, pre-recorded videos

and slides with the quizzes (without answers) were

sent to the students for pre-study. During the lectures,

2-3 LPQs were conducted every 15-20 minutes fol-

lowed by live explanations and discussions of the an-

swers. After the mid term when the students have suf-

ﬁcient experience of learning with my teaching prac-

tice with LPQs, the survey was distributed. Out of the

70 invited surveys, 30 responses were collected but

with 2 invalid ones without any answers. That said,

the later analysis is based on a sample of 28 valid re-

sponses, which was deemed statistically adequate.

Figure 1: The teaching practice using LPQs in the CS mod-

ule where students were surveyed.

Overview of Analysis Approaches. For the 12

multiple-choice questions, we perform the following

quantitative analysis:

• Summarise and presenting the answer distribution

of each question, showing the central tendency

and spread of responses.

• Investigate correlations between questions using

a correlation matrix of Pearson correlation coefﬁ-

cient, and understand which questions have strong

positive or negative correlations.

CSEDU 2025 - 17th International Conference on Computer Supported Education

292

For the 2 ﬁll-in-the-blank questions, not all re-

spondents provide informative answers. Thus, a sim-

ple qualitative analysis are conducted and reported in

the next section.

3 RESULTS AND DISCUSSIONS

All survey data and quantitative analysis code are

publicly available at our project repository

3.1 Data with Basic Statistics

For the 12 multiple-choice questions, the Q1-Q4 are

about general feedback regarding the module, while

the last 8 questions (Q5-Q12) are more speciﬁcally

designed to assess perspectives on LPQs. This divi-

sion of question types may later reveal correlations

between students’ overall perceptions of the module

and their speciﬁc reﬂections on the use of LPQs.

Q1: I Am Conﬁdent I Can Succeed in this Module.

The majority of respondents (about 71.4%) expressed

agreement or strong agreement with this statement,

cf. Figure 2. This suggests most students feel conﬁ-

dent in their ability to succeed in the module. How-

ever, about 28.6% were neutral or expressed disagree-

ment. This indicates a substantial minority may have

lower self-efﬁcacy. This distribution suggests that

while most students are conﬁdent, we should be aware

that some may need more support in developing self-

efﬁcacy. Targeted interventions could identify and as-

sist students with lower conﬁdence levels. More im-

portantly, regarding LPQs, we will later exam if the

level of conﬁdence correlated with how student per-

ceive the use of LPQs.

Q2: I Feel Connected with Other Students and

Teaching Staff on this Module. Responses were

more positive on this question compared to Q1.

Around 85.7% agreed or strongly agreed they felt

connected. A small portion (10.8%) were neutral on

their feelings of connection. This suggests they did

not perceive a strong sense of connection, but did not

actively feel disconnected either. Only 1 respondent

disagreed to some extent, signalling they felt discon-

nected from peers and the lecturer. Again, it would be

very useful to later exam if the feeling of connected

correlated with how student perceive the use of LPQs.

https://github.com/x-y-zhao/LPQ survey study

Q3: I Believe I Am Contributing to and Engaging

Effectively with the Module (e.g., Participating in

Discussions and Other Learning Activities). As

shown in Figure 2, a majority of respondents, 75%,

agreed or strongly agreed that they were actively con-

tributing and engaging with the module. The remain-

ing 25% were neutral, neither agreeing nor disagree-

ing about their participation. So in fact, most stu-

dents responding to the survey did perceive that they

were actively involved and participating in the mod-

ule learning activities. This might hint the positive

outcome of using LPQs, which needs more investiga-

tion later.

Q4: at this Stage in the Module I Understand How

My Learning Will Be Assessed on this Module.

Almost every respondent (27 out of 28) agreed or

strongly agreed that they understand how their learn-

ing will be assessed in the module. Only 1 respondent

was neutral, neither agreeing nor disagreeing with the

statement. This indicates that, despite the extensive

use of LPQs in lectures, it did not confuse students

about how the module would be assessed at the end

of the term. As long as clear statements about as-

sessment are provided in the module speciﬁcation and

reiterated verbally during lectures, the inclusion of

LPQs throughout the course does not appear to ob-

scure the end-of-term evaluation methods.

Q5: How Often Did You Attend this Module with

LPQs? And How Often Did You Attend Other

Modules Without LPQs? As shown in Figure 2,

the majority (64.3%) are neutral in terms of if the use

pf LPQs helps the attendance. A substantial propor-

tion (32.1%) suggests the LPQs may have increased

motivation and engagement, leading to higher lecture

attendance rates. That said, 1 respondent attended

other lectures more frequently without LPQs. So,

while LPQs may have encouraged attendance, they

do not fully explain the variation in lecture attendance

rates. Other factors are likely also at play.

Q6: Did the LPQs Help You Better Understand the

Lecture Material? The vast majority of respon-

dents (approximately 93%) answered “Yes” that the

LPQs helped them better understand the lecture mate-

rial. Only a very small number answered “Not sure”,

indicating they were uncertain about the impact. The

overwhelmingly positive response suggests the LPQs

were broadly viewed as beneﬁcial for comprehend-

ing the lecture content. This aligns with the intent of

using active learning techniques like polling (Arthurs

and Kreager, 2017) to check understanding and clar-

ify knowledge gaps during lectures.

The Impact of Live Polling Quizzes on Student Engagement and Performance in Computer Science Lectures: A Post-COVID19 Study

293

Figure 2: Survey results of Q1-Q12.

Q7: Did the LPQs Help You Stay Engaged During

the Lecture? The majority of respondents (around

85.7%) answered “Yes” that the LPQs helped them

stay engaged during lectures. However, the rest were

uncertain. Overall, the responses indicate LPQs were

broadly effective at keeping most students’ attention

and participation during lectures.

Q8: Did You Feel More Motivated to Participate in

in-person Lectures when LPQs Were Used? Sim-

ilarly to Q7, the use of LPQs motivated participation

for most students, a few were uncertain on their moti-

vation levels, as shown in Figure 2.

Q9: Did the LPQs Encourage You to Study More

Outside of Class? Compared to the very positive

feedbacks in Q7 and Q8, there is a clear drop in the

number of responses with a positive “Yes”, cf. Figure

2. Responses to this question were relatively mixed—

60% answered “Yes”, indicating the quizzes encour-

aged them to study more outside of class, while 40%

were uncertain or feel LPQs did not affect their study

habits outside classes which indicates LPQs have lim-

ited positive impact on study habits outside classes.

Q10: Were the Instructions for Using the Live

Polling Software Clear and Easy to Follow?

Analysing the responses, the majority (∼86%) an-

swered “Yes” that the instructions for using the

polling software were clear and easy to follow. How-

ever, ∼24% were “Not sure”. This suggests that while

the instructions seem adequately clear overall, there is

room for improvement to make them more universally

understandable. Moreover, we exam how this corre-

lates answers to other questions to understand the im-

portance of a clear instruction of using the software.

Q11: Did the LPQs Help You Identify Areas

Where You Needed to Focus Your Study Efforts?

As presented in Figure 2, we got very positive out-

come of this question—93% respondents feel LPQs

helped identify areas needing further study, while

CSEDU 2025 - 17th International Conference on Computer Supported Education

294

only 7% are uncertain. We may conﬁdently conclude

that the majority of students found LPQs useful for

highlighting areas to concentrate their studying on.

Q12: Do You Believe that LPQs Should Be Used

More Frequently in Lectures? The responses

were relatively mixed compared to previous ques-

tions, despite those positive aspects of using LPQs.

Approximately 68% of students answered “Yes” that

LPQs should be used more frequently. Around 29%

were “Not sure” if increased usage was beneﬁcial,

and 1 answered “No”. This suggests that increased

LPQs frequency may beneﬁt some students but risks

overuse for others if not managed carefully.

3.2 Correlation Analysis

To perform quantitative correlation analysis between

the 12 multi-choice questions, we ﬁrst encode the an-

swers into numerical values:

• Strongly Agree =1; Agree=0.5; Neither Agree nor

Disagree = 0; Disagree = −0.5; Strongly Disagree

= −1

• Very often and very often = 0; No often and not

often = 0; Very often and not often = 1; Not often

and very often = −1;

• Yes = 1; Not Sure = 0; No = −1

Intuitively, we encode answers in favour of using

LPQs as positive numbers, neutral answers as 0, and

otherwise negative numbers.

Figure 3 shows the correlation matrix, in which

each correlation coefﬁcient ranges from -1 to +1. A

positive value indicates a positive correlation, a nega-

tive value indicates a negative correlation, and a value

close to 0 indicates little to no linear correlation (Carl-

son and Herdman, 2012). Although there are several

correlation coefﬁcients we can use, we present the

most common Pearson correlation coefﬁcient (Cohen

et al., 2009) in the matrix.

We ﬁrst highlight those positively correlated ques-

tions/answers with sufﬁciently high degree (> 0.3).

As expected, the answers of the ﬁrst 4 questions (Q1–

Q4) regarding general feedbacks of the module are all

strongly correlated, indicating the validity of the re-

sponses collected. The answers to Q1 and Q6, as well

as Q2 and Q6, show a positive correlation. This cor-

relation implies that the extent to which students use

LPQs to understand learning material is positively as-

sociated with both their conﬁdence in being success-

ful and their sense of connection with others in the

lectures. In other words, the more students effectively

utilise LPQs, the more likely they are to feel conﬁdent

Figure 3: The correlation matrix of the 12 multi-choice

questions, showing the Pearson correlation coefﬁcients.

about succeeding and connected with their peers dur-

ing lectures. Q7 and Q8 show a positive correlation,

indicating that if LPQs help a student stay engaged

during lectures, then they are also more likely to moti-

vate that student to attend lectures in person. The pos-

itive correlations between Q8 and Q9, as well as be-

tween Q8 and Q10, indicate that feeling motivated by

LPQs to attend lectures is positively associated with

both being encouraged to study more outside of class

and quickly adapting to using learning software. The

positive correlation between Q11 and Q6 says when

LPQs help the student better understand the learn-

ing material, it also identify the area where the stu-

dent need to focus. Very signiﬁcantly, Q11 and Q10

are positively correlated, showing the clear instruction

on using software positively correlates LPQs help in

identifying areas to focus. Q12 shows positive corre-

lations with Q3, Q4, and Q11 respectively. This says

that students who are in favour of using LPQs more

frequently also tend to report higher engagement in

the module, better understanding of how the module

will be assessed, and that LPQs helped them iden-

tify areas to focus on. In other words, students who

want more regular use of LPQs believe they lead to

greater engagement, clarity on assessments, and abil-

ity to pinpoint knowledge gaps.

While generally all negative correlations among

those 12 questions/answers are not very signiﬁcant,

we highlight two pairs that have correlations smaller

than -0.2—Q5 and Q8, and Q5 and Q9. This indi-

cates: i) Students who attend lectures with LPQs rel-

atively more often than lecturers without LPQs do not

The Impact of Live Polling Quizzes on Student Engagement and Performance in Computer Science Lectures: A Post-COVID19 Study

295

necessarily feel more motivated because of the use of

LPQs. ii) Students who attend lectures with LPQs

relatively more often than lecturers without LPQs do

not feel LPQs encourage them to study more outside

of class. While a rigorous study with more data is

needed to draw accurate conclusions, for now, we can

interpret them as: i) LPQs might have encouraged at-

tendance, but there are likely other relevant factors

that contribute more than LPQs in this regard. ii) Stu-

dents who attend in-person lectures with LPQs more

often may rely too much on them, which diminishes

their motivation to study outside of class.

3.3 Qualitative Analysis

To prevent respondent fatigue and ensure data quality,

limited number of ﬁll-in-the-bank questions should be

used in the survey (Galesic and Bosnjak, 2009). That

said, we included the following two open questions.

Q13: What One Thing Can We Do to Better to

Improve Your Experience on this Module? This

is a question regarding how the students perceive the

module. In-total 9 answers were given out of 28 valid

respondents, covering the points of asking for more

exercises/tutorials, and more interesting examples.

Q14: What Suggestions Do You Have for Improv-

ing the Use of LPQs in Lectures? This question

targeted LPQs, with 10 answers from 28 valid respon-

dents. Notably, all 9 respondents who answered Q13

also answered Q14. Key points include the need for

more accessible web-based LPQs and an increased

number of LPQs per lecture.

Qualitative results suggest that LPQs can inﬂu-

ence student behaviour and engagement. Making

web-based LPQs more accessible with clear instruc-

tions, as highlighted by (Kay and LeSage, 2009), and

increasing their frequency during lectures could en-

hance engagement and learning for some students.

4 DISCUSSION ON USING LPQs

PRE- AND POST-COVID19

Pre-COVID Use of LPQs. Before the COVID19

pandemic, LPQs were increasingly popular as an ac-

tive learning strategy in higher education settings. Re-

search has shown that integrating live polling activ-

ities, where students respond to questions posed by

the lecturers using digital devices, can increase stu-

dent attention, participation, and understanding of the

course materials (Bode et al., 2009; Kay and LeSage,

2009; Miller et al., 2013). One of the pioneering

studies in this area was conducted by (Draper and

Brown, 2004) in 2004. They examined the use of

personal response systems (clickers) in large univer-

sity lectures across multiple disciplines. Their ﬁnd-

ings showed that these systems could increase student

engagement and provide valuable feedback to instruc-

tors. A 2009 review paper by (Kay and LeSage, 2009)

synthesized research on classroom response systems

up to that point. They found that these systems gen-

erally had positive effects on classroom environment,

learning, and assessment, while a detailed list of bene-

ﬁts and challenges are also summarised. (Beatty et al.,

2006) explored different pedagogical approaches for

integrating classroom response systems effectively.

They emphasized the importance of question design

and follow-up discussions to maximize learning ben-

eﬁts. The immediate feedback provided through live

polling also allows lecturers to gauge student under-

standing in real-time and adjust their teaching timely

(Voelkel and Bennett, 2014). In (Lantz and Stawiski,

2014), the study tested clickers’ effectiveness in a

controlled lab setting and found that clicker ques-

tions with immediate feedback signiﬁcantly improved

scores two days later compared to no-clicker controls.

Additionally, the immediate feedback helped partici-

pants not only retain information but also correct lec-

ture misconceptions. The work (Stowell, 2015) com-

pares traditional clickers to mobile-based LPQs and

investigates their impact on student engagement. It

shows that Mobile device polling beneﬁts include dis-

playing questions and class response distributions di-

rectly on students’ screens, lower costs, and suitabil-

ity for open-ended responses. Unlike clickers, some

mobile services also allow “hotspot” questions requir-

ing image-based responses. However, mobile polling

may lead to digital distractions, internet connectivity

issues, and potential costs for students. (Sheng et al.,

2019) ﬁnds students are dissatisﬁed when questions

posed do not stimulate impactful discussions. Caveats

are discussed by (Florenthal, 2019) on the “downside”

of anonymity where some students may ﬁnd it allows

them to disengage and perhaps disrupt learning. The

recent paper (Wood and Shirazi, 2020) identiﬁes of

the main factors affecting student experience of learn-

ing when using audience response systems in general.

New Perspectives in Post-COVID. While LPQs

continue to help maintain student attention and com-

prehension (e.g., Q12 positively correlates Q3, Q4

and Q11), they now play a more critical role in re-

building sense of connections disrupted by extended

periods of remote learning. That is, post-pandemic

students seem to value LPQs not only as learning

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296

tools but also as more essential to re-establishing so-

cial connection with peers and teachers (e.g., cor-

relation analysis around Q2), which were impacted

by the shift to remote and hybrid learning environ-

ments. With remote learning environments offer-

ing more ﬂexibility, many students grew accustomed

to passive engagement modes and self-paced study,

which can make returning to active in-person partic-

ipation more challenging. LPQs thus serve as an es-

sential tool not only for engaging students but also

for re-acclimating them to real-time interaction and

sustained concentration in a physical classroom (e.g.,

correlations between Q7 and Q8).

Additionally, students now place greater empha-

sis on clear instructions and accessibility in digital

tools, reﬂecting a heightened dependency on technol-

ogy for learning during the pandemic (e.g., the cor-

relation analysis of Q10 and Q11). Furthermore, our

study suggests that students are more sensitive to the

frequency and usability of LPQs, preferring an op-

timal balance that avoids overuse (analysis around

Q12). While LPQs previously functioned as intermit-

tent checkpoints for engagement, the study indicates

that students now feel overwhelmed when quizzes are

overly frequent, potentially viewing them as interrup-

tions rather than engagement aids. This ﬁnding im-

plies that students’ tolerance for LPQ frequency has

been inﬂuenced by the remote learning environment,

where they had more control over when and how they

interacted with course material.

5 THREATS TO VALIDITY

Construct Validity. It refers to the extent to which a

survey instrument measures the theoretical construct

or concept it claims to be measuring. In this study,

the use of self-reported survey data is subjective and

prone to self-reporting bias that may pose a threat.

Students may have responded more positively due

to wanting to please the lecturer who is also the re-

searcher. To mitigate these two threats, we assure

respondents that their responses will be kept conﬁ-

dential and anonymous. This can reduce the fear of

social judgement and encourage more objective and

accurate reporting. Students who had more positive

views on LPQs may have been more inclined to take

the survey, while others with negative views may be

underrepresented. To mitigate this response bias, we

have sent reminder messages to non-respondents to

encourage their participation during the 3-months sur-

vey period, and tried to clearly communicate the pur-

pose of the survey and its importance to all students

regardless of their views.

Internal Validity. Threats may correspond to bias

in establishing cause-effect relationships in our sur-

vey. When interpreting the results of our correlation

analysis, we are fully aware that “correlation does

not imply causation” is a fundamental principle in re-

search and statistics. Confounding variables, i.e., fac-

tors other than the use of LPQs (e.g., physical learning

environment and teaching material quality) may have

inﬂuenced outcomes like attendance and engagement.

To mitigate such threat, we plan to do Randomised

Controlled Trials in the future by carefully consider-

ing and addressing confounding variables in the de-

sign and analysis. In this preliminary study with lim-

ited data, we only draw correlation conclusion.

External Validity. Factors limiting generalisability

threaten external validity. The selection bias (e.g.,

only a group of UG CS student from one University

was study) and small sample size are two threats in

this regard. In addition, only one polling software

(itempool.com) was studied that also poses a threat.

To mitigate them, more sample needs to be collect

with diversiﬁed data representing more students and

software tools. In this preliminary study, we have ex-

plicitly discussed the limitations related to our sam-

ple’s representatives.

6 CONCLUSION

After nearly 3 years of remote education, student be-

haviours and preferences may have shifted, neces-

sitating a re-evaluation of LPQs in the context of

COVID-19. This study surveyed CS UG students who

attended lectures with and without LPQs, focusing on

engagement, learning outcomes, polling frequency,

and its correlation with course perceptions. The quiz

questions were factual and objectively answerable.

Preliminary ﬁndings show that while live polling

improved attendance and comprehension for most

students, it was not the sole factor. Overuse risks di-

minishing motivation, and clear software instructions

are critical. Although students found polls broadly

beneﬁcial, the pandemic’s impact underscores the

need for renewed investigation.

This study ﬁlls a literature gap by examining ac-

tive learning technologies in the post-COVID-19 con-

text, offering insights into the evolving role of LPQs

in CS education. Future work includes ongoing mon-

itoring, mitigating validity threats, and applying ad-

vanced analyses, such as clustering and factor analy-

sis, as more data becomes available.

The Impact of Live Polling Quizzes on Student Engagement and Performance in Computer Science Lectures: A Post-COVID19 Study

297

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