What We Learned from the Abrupt Switch to Online Teaching Due to the

COVID-19 Pandemic in a Post-secondary Computer Science Program

Jalal Kawash, Joshua Horacsek and Nelson Wong

Department of Computer Science, University of Calgary, 2500 University Dr. NW, Calgary, Alberta, Canada

Keywords:

Computer Science Education, COVID-19, Online Teaching and Learning, Zoom.

Abstract:

Online learning has been extensively researched, and online educators have a wealth of resources to build

upon. However, when the COVID-19 pandemic hit, we were forced to abruptly convert course delivery from

face-to-face to online. To make matters worse, this occurred in the middle of the semester, and the majority of

us were not prepared — the majority of us had never taught online, nor have we received the required training

to do so. This abrupt change also made it challenging for students which, in turn, posed additional challenges

for educators, especially in relation to navigating student expectations. Unlike students who sign up for an

online course, these students were also caught unaware by the switch, and online learning was new to most of

them. We reﬂect upon this experience, paying special attention to the challenges associated with the discipline

of Computer Science as well as those faced by teaching assistants. The COVID-19 pandemic will come to an

end, but this change to education will stay with us. Hence, we share the lessons we learned.

1 INTRODUCTION

The COVID-19 pandemic drastically changed the

way we teach in the Department of Computer Sci-

ence at the University of Calgary. Mass closures be-

gan in Canada mid-March 2020, and our department

was abruptly forced to switch to online course deliv-

ery as a result. The majority of the instructors within

our department had never previously taught in an on-

line format, and likewise did not have any training for

online teaching. The switch caught the majority of

us off-guard; our plans for lectures, tutorials, and labs

were already in place and operational for a face-to-

face delivery model. The abruptness of the closures

forced many of us to quickly recalibrate our teach-

ing structure without thoroughly vetting our changes

for the new delivery mode. Combined with the afore-

mentioned lack of training, many of us experienced

hiccups with the transition.

Like any other discipline, Computer Science has

its own unique teaching challenges. Writing pa-

pers, formulating theses and/or performing experi-

ments and quantitative/qualitative analyses are very

small components of undergraduate Computer Sci-

ence course work, if part of it at all. Most Computer

Science courses are heavily structured around build-

ing technical problem solving skills. Of course, not

all courses in Computer Science are structured in the

same way; some focus more on theory than practice

and some are quite the opposite. However, the fo-

cus on problem solving is a strong part of classroom

activity outside of lecture. Tutorials are meant to be

hands-on sessions in which teaching assistants (TAs)

build upon material covered in lectures and provide

small-group and one-on-one support to students.

No class structure is perfect — one should always

be evaluating and reﬁning one’s teaching methodol-

ogy. That being said, many instructors and TAs in

our department have been teaching in the same face-

to-face environment for many semesters and have had

ample time to determine which techniques work best

for them. The practices that instructors and TAs de-

veloped have largely been disrupted by the move to

online learning during the pandemic. In our depart-

ment, all teaching practices have been moved online

to Zoom (Zoom, 2020), and unfortunately many of

the techniques that instructors and TAs have devel-

oped have not necessarily translated to the new deliv-

ery mode.

Research tells us that our face-to-face teaching ex-

perience may not be transferable to online settings

without modiﬁcations. A proper command of the un-

derlying technologies, an understanding of the new

social orders, and the ability to harness the media-

rich resources are all required to effectively teach

online (Jump and Schedlbauer, 2020; Nelson et al.,

148

Kawash, J., Horacsek, J. and Wong, N.

What We Learned from the Abrupt Switch to Online Teaching Due to the COVID-19 Pandemic in a Post-secondary Computer Science Program.

DOI: 10.5220/0010379401480155

In Proceedings of the 13th International Conference on Computer Supported Education (CSEDU 2021) - Volume 2, pages 148-155

ISBN: 978-989-758-502-9

2005). Not all educators are familiar with online

teaching and its associated challenges; even fewer are

actually trained to perform it (Bowen, 2010). The

institution also needs to provide the proper support

and environment for effective online teaching, such

as standardization (Creanor and Littlejohn, 2000).

Learner-centered education becomes more important

in online environments (Creanor and Littlejohn,

2000; Donald et al., 2002; Herrington and Oliver,

2020; Sharma et al., 2020). Salmon identiﬁes the es-

sential characteristics needed by educators to succeed

online (Salmon, 2000). These are (1) understanding

of the online environment, (2) technical command of

the online platform, (3) online communication skills,

(4) content expertise, and (5) possession of certain

personal attributes that allow the educator to thrive

in an online environment. Hence, effective online

teaching requires preparation and support that were

not available during the sudden shift imposed by the

COVID-19 pandemic.

A unique challenge that many of us faced during

the pandemic was the abruptness of the transition to

online learning. The sudden shift meant that educa-

tors already had lecture and assessment plans in place

assuming a face-to-face delivery. Scrambling in the

middle of the semester to re-adjust lesson plans and

modify assessment methods can only add to the chal-

lenges of online teaching. There has been no previ-

ous event comparative to the scale of COVID-19 that

has necessitated such a large shift to online learning,

as such research is required to document and under-

stand ts unique challenges. These challenges do not

only apply to students but also to instructors and TAs

alike. To our knowledge, online teaching challenges

for TAs were not previously studied except in massive

open online courses (MOOC) context (see (Ntourmas

et al., 2018) and the references within). Unlike in

MOOCs, our TAs had already planned their instruc-

tion for a face-to-face delivery when the pandemic hit

and the vast majority of them have never received any

training for online instruction.

Face-to-face and online assessment methods can

be substantially different. One speciﬁc challenge in

many Computer Science courses is that, when not

proctored, students have the ability to test code snip-

pets and answer questions without demonstrating any

learning. For example in programming courses, it is

popular to ask students to ﬁnd the output of a code

segment or correct its syntax errors (see Figure 1 for

example questions). It takes a few seconds for a stu-

dent to copy or type the snippet into a skeleton pro-

gram, compile and execute the code, then correctly

answer the questions without giving any thought, let

alone demonstrating understanding. Educators need

Q1. What is the output of the following program segment?

Q2. Correct the syntax errors in the following program seg-

ment:

Q3. Which of the following code segments outputs 2 11?

Figure 1: Sample questions from popular question types

used in computer science exams (C language is used).

to innovate when designing online assessment tools

and we generally do not have the luxury of time and

resources in a sudden change due to a pandemic.

While student challenges are as important, this pa-

per only discusses the challenges faced by our teach-

ing staff. The second author of this paper is a lead

teaching assistant (TA) who is responsible for mentor-

ing the remaining TAs in the department. The remain-

ing authors and instructors. One instructor has over

two decades of teaching under his belt and the other

is fairly junior. Hence, we provide a fairly diverse rep-

resentation of the teaching power in our department.

Furthermore, TAs form an intrinsic and crucial com-

ponent of our teaching capacity, thus reﬂecting on our

TAs’ experience is important.

In Canada, the academic year includes two main

semesters. The Fall semester runs from September

to December and the Winter semester spans the pe-

riod of January to April. There are two additional

short semesters: Spring (May and June) and Summer

(July and August). Our reﬂection covers experience

What We Learned from the Abrupt Switch to Online Teaching Due to the COVID-19 Pandemic in a Post-secondary Computer Science

Program

149

from two semesters: the Winter 2020 semester, during

which the pandemic hit in the middle of the semester,

and Spring 2020, which starts immediately after the

Winter semester leaving little time for preparation.

As of this writing, the world is still battling

COVID-19 with a vaccine light starting to appear at

the end of the tunnel. The status quo of teaching and

learning remains unchanged and the lessons learned

from this experience of the abrupt change continue

to be valuable. In addition, the pandemic has given

many educational institutes the opportunity to start

pondering with switching some or all of their pro-

grams to an online model. Our shared experience,

conclusions, and recommendations can be valuable in

these situations.

The remainder of this paper is organized as fol-

lows. In Section 2, we give a description of our de-

partment contextualizing our reﬂection. Our unique

TA mentorship program is discussed in Section 3. The

reﬂection on our experience is provided in Section

4 and recommendations are discussed in Section 5.

Section 6 concludes the paper.

2 THE DEPARTMENT

The University of Calgary in Alberta, Canada is a re-

search intensive institute with a population slightly

over 35,000 students, more than 76% of which are

undergraduate students. The Department of Com-

puter Science offers degrees in Computer Science and

Data Science. The vast majority of students are in

the Computer Science stream. The department is a

house for 50 full-time faculty members. In the Win-

ter 2020 semester, our department had 1,202 students,

almost 88% of which were undergraduates and of-

fered 47 courses with 54 sections at the undergrad-

uate level and 14 graduate courses with 21 sections.

The average class size in Winter 2020 was 64 students

for undergraduate courses and 7 students for graduate

courses. In Spring 2020, the department offered 14

undergraduate courses in 21 lectures and no graduate

course, with an average class size of 84 for under-

graduate courses. Note that the department offers a

substantially lower number of courses in the Spring

and Summer semesters due to their condensed length.

With very few exceptions, every undergraduate

course in the department has tutorials, where the class

is divided into smaller sections of at most 25 students.

A typical course includes in a week: 150 minutes of

lectures where the whole class meets with the princi-

pal instructor for the course and 100 minutes of tu-

torial time where the smaller groups meet with their

designated TAs. TAs work in tandem with the princi-

pal instructor. Typically, tutorials are meant to pro-

vide hands-on experience to students, which other-

wise cannot be offered by the instructor given the rel-

atively large class sizes. TAs are graduate students

in the department and are assigned to courses at the

beginning of the semester. Every admitted graduate

student is offered a teaching-assistantship within the

department for a period of 2 years (for M.Sc. stu-

dents) and 4 years (for Ph.D. students). That is, the

TA program has two direct objectives: (1) providing

graduate students with a form of ﬁnancial support in

return for the work they provide to the department and

(2) making use of this human/brain power of graduate

students to support our faculty with their teaching.

3 TAiR PROGRAM

Realizing the importance of tutorials as an integral

part of the learning experience for students, and given

the fact that the majority of our TAs do not have much

prior teaching experience (as a matter of fact, most

ﬁrst year graduate students do not have any teach-

ing experience), in 2013 the department established a

unique program to mentor and support TAs (Stephen-

son et al., 2014). The program is called TA in Res-

idence (TAiR for short). The TAiR program has

evolved over time with successive improvements, but

it mainly consists of hiring an experienced and often

stellar TA to be a mentor for the remaining TAs, pay-

ing special attention to rookies and under-performers.

Currently, the program consists of:

1) Conducting regular class observation visits in

which the TAiR visits and observes tutorials. An ob-

servation is then immediately followed by a one-on-

one meeting between the TA and TAiR. The TAiR

provides feedback to improve a TA’s teaching prac-

tices. Follow up visits are common.

2) Hosting regular experience share program (ESP)

sessions, where the TAs have informal coffee gath-

erings, moderated by the TAiR, to share and discuss

their experiences. It is an opportunity for less expe-

rienced TAs to seek support and advice from more

seasoned TAs. For the longer term, the ESP intends

to create a community of practice among TAs; and

3) Requiring the participation in teaching develop-

ment workshops that can be tailored to our TA needs

or can be offered outside the department as well as

long as their focus is on teaching and learning.

TAs sign contracts at the beginning of each

semester outlining their time-commitment and the du-

ties required from them. A speciﬁc number of hours

in these contracts are explicitly dedicated for TAs’

professional development.

CSEDU 2021 - 13th International Conference on Computer Supported Education

150

The second author of this paper was serving as a

TAiR during the Winter and Spring 2020 semesters.

The ﬁrst author was the Associate Head for Teaching

and Learning who was supervising the TAiR program.

4 REFLECTION

This section is a qualitative, reﬂective discussion

based on our experiences, instructors and TAs. These

are our own experiences as well as impressions we

obtained from discussions with our colleagues. First,

we provide observations from lectures. Observations

from tutorials are given in Subsection 4.2.

4.1 Instructors’ Experience

Assessment: The abrupt change to online teaching

created a challenge for instructors to stick to their

assessment plans. For instance, some instructors

had ﬁnal exams planned, but not all instructors were

able to stick to their predetermined plans. In some

courses, unproctored exams allow students to use re-

sources (development environments including com-

pilers and online tools) that are otherwise unavailable

in a traditional exam environment; these tools can al-

low students to ace the exams without demonstrating

any mastery of the learning outcomes. This deemed

some multiple-choice or short-answer questions use-

less since students can type the code, test it, and an-

swer certain questions without demonstrating any un-

derstanding of the material. We have already given

some examples in Figure 1. Designing thoughtful and

alternative ways of online assessment is difﬁcult in the

ﬁrst place. The short period of time that was given to

instructors to switch made this challenge even more

aggravated. Many instructors resorted to revisiting

their grade distribution to allocate more marks to out-

of-class components, such as take-home assignments.

This Computer Science speciﬁc challenge of hav-

ing tools available to students that allow them to an-

swer exam questions without demonstrating learning

lead some of us to resort to project-based learning

during the Spring semester avoiding exams altogether.

However, the project-based approach also introduced

its own challenges. Project-based learning requires

more commitments and extra resources that allow the

instructor to attend to student requests throughout the

semester as well as evaluating these projects at the end

of the semester. Many of us struggled to ﬁnd the time

to cope with these requests, especially given often un-

reasonable student expectations.

Expectations: The switch to online delivery created

unreasonable expectations from many students in re-

gard to instructor and TA availability and in terms of

content. Students expected us to be available 24/7.

Some students were inclined to ask for immediate

Zoom meetings outside ofﬁce hours expecting us to

always honor such requests. This was aggravated on

homework assignment and project due dates. Some

of the due date times were set at midnight and we had

students asking for immediate Zoom meetings a few

hours or minutes before the deadline! The expecta-

tions for responding to email were not better. Many

students expected instantaneous replies to their email

messages. One student wrote complaining to the in-

structor that it took the TA almost an hour to reply to

the student’s email. We have never experienced such

expectations in the face-to-face delivery model. It is

apparent that something in the online environment is

encouraging students to have such unreasonable ex-

pectations.

In terms of content, some students expected that

the course material would be watered down due to

the pandemic. This created friction while enforc-

ing our position that there are course objectives and

learning outcomes that must be achieved regardless

of when and how the course is offered. This resulted

in some instructors being called “inconsiderate”, to

say the least. This is an interesting shift in expecta-

tions from the perspective of some students. They ex-

pected more from the instructor but thought less was

expected from them. Nevertheless, we emphasize that

this experience was not universal among all students

or in all courses.

Interaction and Behavior: Some of us did not see

the face of a single student, or hear their voice dur-

ing (online) lectures for the entire semester. In one

course, where the students were required to work in

groups during lectures, through the “breakout rooms”

feature in Zoom, all students carried out the group dis-

cussion in the chat box. In another case where the in-

structor gave priority to questions asked outside the

chat box, attending to the latter at speciﬁc times dur-

ing the lecture, many students chose to ask questions

in the chat box, sacriﬁcing the option of having their

questions answered immediately rather than in a de-

layed fashion. Very few, if any, of those who went

for questions outside the chat box chose to turn on

their cameras. This seemed to be more prevalent in in-

troductory and large-enrollment courses. Upper level

courses tend to have smaller class sizes and these stu-

dents have likely worked together previously in other

courses. For such courses, it was not as challenging

to engage students. Zoom allows users to change their

user names, and some students chose cryptic names.

Hence, even when using the chat box to ask questions,

some students were unidentiﬁable.

What We Learned from the Abrupt Switch to Online Teaching Due to the COVID-19 Pandemic in a Post-secondary Computer Science

Program

151

This sense of anonymity also resulted in an in-

creased behavior of rudeness toward the instructor.

The fact that students were unknown to, unseen, or

unheard by the instructor gave a sense of immunity to

unacceptable behavior and sometimes the use of abu-

sive language (Postmes et al., 2001). In face-to-face

interaction, students tend to observe certain norms of

social interaction that were no always followed with

online interaction. We cannot dismiss as well the

stresses that the pandemic placed on students as a con-

tributor to such behavior as well.

Indirect Feedback: A critical aspect of teaching that

instructors take for granted in a face-to-face setting is

the indirect feedback received during lectures. Such

feedback includes students’ facial expressions and

body language. Many of us did not realize how heav-

ily we have been depending on this kind of feedback

to assess the degree of student engagement and under-

standing. In an online settings, most of the indirect

feedback has become limited or unavailable. In order

to approximate feedback in an online setting, students

must have video cameras and must be willing to turn

them on. However, not all students had the equip-

ment, and for those who did, only a very small por-

tion was willing to turn them on. As mentioned ear-

lier, some of us did not see a student face or hear their

voice for a whole semester. One of us started the term

by encouraging students to turn on their cameras and

explained why having the camera on can help them

better engage and learn. As a result, more students

turned their cameras on. However, the Zoom monitor

cannot show more than 25 students simultaneously.

Therefore, relying on indirect feedback in these on-

line teaching environments was not an ideal way for

the instructor to receive the required feedback.

We incorporate a class room response system

(CRS) into the lectures, requiring students to work in

groups to solve graded exercises. The participation in

the breakout rooms was at a high rate. One of us ob-

served that with the exception of less than handful of

students, the whole class opted to participate in break-

out rooms. It is worth mentioning that the breakout

rooms were generated randomly and were not con-

sistent throughout the term. It is possible for those

who did not participate in breakout rooms to still com-

municate with their piers through other means out-

side the Zoom environment. Some students prefer to

maintain a consistent group to work with throughout

the term. As we mentioned earlier, many of those

who joined the breakout rooms carried out discussion

through texting only. The use of CRS has been shown

to engage students (Kawash and Collier, 2019) and

improve their content retention (Collier and Kawash,

2018) in a face-to-face setting. In spite of the absence

of concrete data, we believe that these beneﬁts were

maintained in an online environment.

4.2 Teaching Assistants’ Experience

Now, we discuss our experience from the sudden

change to online teaching as it relates to tutorials and

TAs. Recall that tutorials are conducted by TAs to

complement lectures and consist of smaller groups of

students. Zoom was also the platform for teaching tu-

torials. The following is the product of about 15 tuto-

rial observations from the Winter 2020 semester (the

semester in which we transitioned to online learning),

about 11 tutorials from the Spring 2020 semester,

and interviews with multiple TAs throughout the pan-

demic.

Platform Familiarity: Since the transition to on-

line learning occurred midway through the Winter

2020 semester, TAs in the department were abruptly

dropped into an online learning environment without

any training. This became apparent during TA obser-

vations; TAs were generally unfamiliar with Zoom.

This includes, but is not limited to Zoom features

such as: screen-sharing, breakout rooms, and wait-

ing rooms. Often TAs acknowledged that they were

aware of such features, but missed the implications

of these features. For example, TAs were aware of

screen-sharing, but were not aware of the screen an-

notation or remote control functions that come along

with it — these features can be particularly helpful

in one-on-one sessions with students, especially when

helping students debug their code. Breakout and wait-

ing rooms were not used by any TA during observa-

tions.

Behavior: There is a diversity of tutorial types in our

courses, but they all contain some common compo-

nents. Many include a “lecture” component, an exer-

cise component, and/or a hands on component. The

lecture component is perhaps the least affected com-

ponent through the transition. In this regard, Zoom is

an adequate platform for this type of interaction, how-

ever when it comes to exercise and hands on compo-

nents, there is a noticeable gap. Hands on components

require more interaction from students, yet students

were reluctant to enable voice chat — instead prefer-

ring to use the text chat within Zoom. During obser-

vations, not a single student enabled video chat, with

the only excepting being an instance of screen sharing

in which the student shared their screen with the class

(an option which we would rather avoid.)

Text chat is the mode of communication that stu-

dents overwhelmingly preferred. During the post ob-

servation meeting, many TAs felt text chat was an in-

efﬁcient use of time, stating that it was much easier

CSEDU 2021 - 13th International Conference on Computer Supported Education

152

and faster for TAs to interact with students using voice

chat. One TA had gone so far as to disable the text

chat feature of Zoom in an effort to encourage more

audible participation in their tutorial. Since many TAs

were recording their tutorials for later distribution,

disabling the zoom chat had the secondary beneﬁt of

archiving the tutorial’s discussion, since the text chat

is ephemeral and not recallable in any way. However,

one must take care in disabling the chat. Some stu-

dents may not have proper audio equipment, or some

may reside in noisy environments in which it is not

feasible for a student to participate via audio. While

it was uncommon, some students did choose to turn

on their microphone. However, if a student did speak

during a tutorial, it was because the TA had already

built an explicit repertoire with that student.

Similar to lectures, there was also the expecta-

tion of quick turn-around times for help outside of

class, mostly via email. These expectations were rel-

atively consistent among tutorials. In contrast to lec-

ture, TAs did not report much friction or rudeness

between themselves and students. This is likely be-

cause the group of students TAs teach is signiﬁcantly

smaller than that of an instructor, and it is easier to

build closer relationships with students, even in an on-

line setting.

Attendance: Attendance numbers were roughly on

par with in person tutorials, however it is unclear

whether or not students were physically present at

their machines during tutorial. The lack of any visual

feedback for TAs made it hard to gauge whether or not

students were not only present but also whether or not

they were understanding the material. Informally, one

TA asked their tutorial students to type in chat if they

were present, of the 15 students in the Zoom session,

less than 50% responded.

One idea would be to make tutorial attendance

mandatory, however, zoom makes it very easy to log

in, then walk away from a tutorial. From the observed

tutorials, making tutorial attendance mandatory was

an ineffective way of engaging students; attendance

was higher, but participation was generally low across

all tutorials. However, another possible solution is to

introduce small and simple graded exercises into tu-

torial structure to incentivize staying on track — the

tutorials with the highest attendance and the highest

participation were ones that had helpful exercises in-

corporated into their class structure.

One-on-One Aspect: Overall, the weakest compo-

nent of tutorials was the one-on-one aspect. TAs

found it difﬁcult to interact with students in the way

that they were normally accustomed to in person.

With face-to-face delivery, a TA often looks over a

student’s code and provides the student with feed-

back or hints as to why it is not behaving as expected.

In person, this simply involves sitting next to a stu-

dent, having them explain their thought process, and

providing expert feedback on whether there is an is-

sue with their thought process, or how they have ex-

pressed their thoughts in code.

Through Zoom, this translated to students posting

their code in the chat (either privately or to the en-

tire tutorial). Obviously, posting code for the entire

class to see is a unacceptable; this may reveal sensi-

tive information to other students, either in the form

of solutions to assignment problems, or sensitive in-

formation such as the student’s institution ID. Aside

from these concerns, it is very difﬁcult to read code

through Zoom’s chat, since it does not properly for-

mat and highlight code for maximal readability. Some

students shared their code with the TA via e-mail,

which can help with readability, but this too has prob-

lems — it creates another non-standard process in the

work ﬂow of helping students. We say non-standard

because it is unclear on how the student should/will

communicate: will they send the TA a source ﬁle? A

simple text ﬁle? A zip archive? For larger classes,

looking through this amount of code can burden the

TA with a large amount of outside hours work.

Screen sharing was perhaps the most simple and

elegant option provided by Zoom that can solve these

problems, but students were somewhat reluctant to

share the screen of their personal computers (al-

though, during observation there were a few instances

where students globally shared their screen to the en-

tire tutorial). However, the lack of proper tools to

annotate a student’s code makes this less useful than

one would hope. When helping a student in person,

one often physically points to errors in code either by

hand or by using the student’s mouse; some also com-

monly write small comments in students’ code indi-

cating where logical ﬂaws are. Zoom does have the

ability to allow a TA to annotate a student’s shared

screen but TAs were generally unaware of this fea-

ture. Moreover, the tools Zoom provides are difﬁcult

to use via keyboards and mice. Some TAs have noted

that tablet computers would have been helpful in this

regard, but providing every TA with a tablet is not

a viable option. There is a feature within Zoom to

remotely control students’ screens, but TAs reported

that they were worried that students would feel this as

an invasion of privacy.

More judicious use of screen sharing could fa-

cilitate better one-on-one interactions, but there also

needs to be an environment in which students feel

comfortable sharing their screens. Recall that Zoom

has a feature called “breakout rooms” that allows one

to group participants into private rooms. This could

What We Learned from the Abrupt Switch to Online Teaching Due to the COVID-19 Pandemic in a Post-secondary Computer Science

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153

be used to conduct one-on-one sessions, providing the

required privacy. However, TAs had noted that this

feature felt more suited to assigning groups to work

on problems. Another feature that Zoom supports is a

“waiting room” where students are kicked out into a

lobby and the TA may control who they interact with

on a one-on-one basis. TAs chose not to use it since

it felt abrupt, disrupted the ﬂow of tutorials, and there

is no mechanism in Zoom to queue students.

5 RECOMMENDATIONS

5.1 Advice Regarding Lectures

Based on the observations discussed in Subsec-

tion 4.1, we recommend the following: 1) Set expec-

tations for instructor and TA availability. Just because

it is an online course, it does not mean that the teach-

ing staff are available 24/7 to answer questions. The

unreasonable expectations that they are always avail-

able will not only generate dissatisfaction from stu-

dents, but will also burn out the teaching staff. Deal-

ing with student complaints will simply emotionally

drain the teaching staff. Students should be encour-

aged to make use of designated ofﬁce hours. Email

response policy must be also clearly stated and com-

municated to students at the start of the semester. We

ﬁnd also that reminders are sometimes necessary.

2) Set expectations for course content. Courses

have certain objectives and outcomes that must be

achieved, and students need to demonstrate that they

meet the required bar regardless of how the course is

delivered. This must be explained to students at the

beginning of the semester with reminders throughout

the semester to reinforce the appropriate expectations.

3) Give priority to voice/video interaction over text

message interaction during lectures. Questions asked

with voice/video are often timely to the subject at

hand. Rarely a student will make the effort to ask such

a question when it is irrelevant to topic at hand. How-

ever, this is not the case for chat box questions. We

found that there can be a delay between when the rel-

evant topic was discussed and the when the question

was asked. Students also do not hesitate to through

any question into the chat box (something relevant to

an assignment, grading, personal, etc · ··, but is irrel-

evant to the topic being discussed.) These questions

often interrupt the ﬂow of the lecture. Interrupting the

ﬂow of lectures is not desirable and can lead to stu-

dent complaints. Hence, specify certain intervals in

the lecture, depending on its ﬂow, to attend to these

questions.

4) Incorporate a CRS component into your lecture.

The use of CRS allows the instructor to break the

monotone of an online lecture. It is also a great mech-

anism to provide two-way feedback. Feedback to the

students to test their understanding of the subject mat-

ter and feedback to the instructor. The importance of

the latter is magniﬁed in online delivery due to the

lack of feedback we receive from body language in

face-to-face format. Better yet if some or all of the

CRS questions are designed as group activities.

5) Utilize breakout rooms or other similar functions

to perform in-class group activities. This can be com-

bined with CRS activities or using polling features.

6) Refrain from using traditional exams for assess-

ment, especially in courses that rely heavily on pro-

gramming. Design of programming questions, as we

discussed in the Introduction section, is tricky in an

unproctored environment. Writing code from scratch

can be more effective than ﬁnding the output or cor-

recting errors. However, be mindful to design ques-

tions that require application and synthesis skills and

whose answers cannot be readily pulled from readily

available online resources. If you have the resources,

converting the online course to project-based learning

would be more effective.

5.2 Advice Regarding Tutorials

Based on the observations of Subsection 4.2, we rec-

ommend the following for TAs:

1) Be clear with how you plan to conduct your tutori-

als, and be clear about your expectations in terms of

participation and use of the platform. That is, if you’d

like students to use screen sharing, be clear about it

and set that expectation, but again, prepare to be ﬂex-

ible. Set these expectations as early as possible.

2) Be explicit and direct with your schedule and tuto-

rial structure. If you choose to use waiting rooms for

one-on-one sessions, make sure you allocate time for

that and inform students about the breakdown — the

intention is to make the tutorial feel continuous when

you force everybody out into a waiting room.

3) Try to use screen sharing and annotation tools in

one-on-one sessions, but be ﬂexible since not all stu-

dents will be comfortable sharing their screen.

4) Try to incorporate exercises into your tutorial struc-

ture, and make them worth some small amount of

the student’s ﬁnal grade. If you have no freedom to

change the grading structure of the course, incentivize

this in other ways: make exercises directly relevant to

assignments and be explicit about that to the students.

Do not solve their problems for them, but give them

problems that require the same skills of problem solv-

ing needed in assignments

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Considerations for instructors:

1) Ensure that the material that you would like cov-

ered is explicit and delivered promptly to the TAs

— TAs need more preparation time in order to work

within the constraints of online learning.

2) Try to incorporate some amount of graded exer-

cises in your plans for tutorial. Or, at the very least,

provide TAs a small fraction of the ﬁnal course grade

to to use it for “participation” marks and some free-

dom to assign these marks to students.

6 SUMMARY

In this paper, we shared what we, as educators,

learned from the abrupt change of teaching modality

— from in-person to remote teaching — in a com-

puter science program. We provided a brief descrip-

tion of our department and our TAiR program in-

tended to mentor and support teaching assistants. We

reﬂected on our (instructors’ and teaching assistants’)

experience and provided recommendation to improve

online teaching. While the pandemic will not last for-

ever, and we surely hope it will be over sooner than

later, it may as well have lasting effects on teach-

ing and learning and the society as a whole. More-

over, it is not unreasonable to expect another pan-

demic at some point in the distant future; the lessons

we learned now may help us then. The pandemic also

gave us an opportunity to think of teaching and learn-

ing in a context that some of us we would not have

considered in normal times. It is conceivable that

some traditional institutions may realize the ﬁnancial

beneﬁts of remote teaching, and they may adopt it in

full or in part post-pandemic. Some of the lessons we

learned beneﬁt others during the pandemic, but also

they can be beneﬁcial in the post-COVID-19 times.

ACKNOWLEDGMENTS

We are thankful to our colleagues, instructors and

teaching assistants, for the valuable discussions.

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What We Learned from the Abrupt Switch to Online Teaching Due to the COVID-19 Pandemic in a Post-secondary Computer Science

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