Facing Forward: How Student Experiences with Emergency Remote Teaching and Learning Can Be Used to Improve Quality Online

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Brief Abstract

While the full impact of COVID-19 on education is yet to be seen, there has been increasing data on how students reacted to the changing post-secondary environment. This session explores how student experiences may be used to reinforce our best practices for online teaching and inform faculty development initiatives.


Erika Ram is an Instructor and eLearning champion within the School of Computing and Academic Studies at the British Columbia Institute of Technology. She has spent over eight years working in higher education, holding positions such as Research Assistant, Program Assistant, Program Coordinator and Faculty member. Her current role allows Erika to combine the practical application of pedagogical theory and effective teaching and learning principles with information technology, program and course development, graphic and web design, and problem-solving. In 2020 Erika graduated from Simon Fraser University with an MEd in Educational Technology & Learning Design and has since begun her journey into educational research. Her research interests include eLearning design practices, agency in technology adoption and use, STEM education, student self-efficacy, self-motivation and self-regulation.

Extended Abstract

Over the past year and a half, the COVID19 pandemic has forced an unprecedented number of educators to transform their lessons into online versions in a short period of time. During this time, staff and faculty have been collecting data through surveys, interviews, and focus groups to identify areas for development in our student services and educational technologies. Despite this growing body of research, it was unclear how the institute or individual departments could use it to inform and craft faculty development initiatives or best practices for online teaching.

The purpose of this study is to explore the impact of emergency remote teaching and learning strategies on student experiences as a whole– and identify emergent themes to inform and improve faculty development initiatives related to online teaching and learning.

The primary research questions are as follows:

(1) How do Students characterize their learning in online courses during COVID19?

(2) What dichotomies and similarities exist between Student experiences of emergency remote teaching and learning and OLC online course best practices?

(3) How might perceptions of Student experiences in online courses inform faculty development initiatives?

This project emerged out of trying to answer the question, "how can we improve our online course offerings for our students and are there any best practices we need to institute in our department?" The online education offerings during the COVID19 pandemic fell in a grey area between the initial emergency remote transition and fully-fledged online courses. Looking at students' experiences during this time is one step towards continuously improving our online offerings.

The information produced from this study may help develop best practices, resources, and professional development opportunities to help instructors design their online courses and enhance instructional quality online.


This study used a mixed-method exploratory approach to better understand student experiences of the emergency pivot to remote teaching and learning. This approach incorporated an initial qualitative phase of data collection, and the results helped formulate a mix of closed, open-ended and Likert scale survey questions.

By including quantitative data with qualitative data, students are provided with the opportunity to participate in the project and shape future development initiatives in a way that values their insight, knowledge, and experience.

A framework approach was implemented to manage and analyze data over five stages using data analysis software, NVivo (Release 12.0). This approach was chosen because (a) it can be used with a wide variety of narrative methods of collecting data, such as open surveys, interviews, focus groups, and observations and (b) it is not aligned to a particular epistemological, philosophical or theoretical approach (Hackett & Strickland, 2018).

The steps for analysis were:

·        Step 1: Familiarisation

o   Initial data was reviewed to get familiarised with the content and obtain a broad overview of participants' responses.

·        Step 2: Construct a thematic framework

o   A list of topics and ideas that emerged during the first stage were reviewed to identify the initial thematic framework or coding index of themes and sub-themes.

·        Step 3: Index and sort data

o   Survey results were then reread and coded according to the coding index identified in Step 2.

·        Step 4: Summarize and display data

o   Thematic charts were created, including extracted quotes and relevant comments. These were examined in conjunction with any statistical survey data from closed-ended and Likert scale questions.

·        Step 5: Map and interpret data

o   Finally, more charts were created, including mapping and interpretation of the data, by going back across the data to obtain and clarify information and select relevant and appropriate quotes

Key Findings

The primary overarching finding of the research conducted throughout 2020 is that the student experiences of the shift to online course delivery in response to the COVID-19 pandemic directly aligned with validated suggestions for measuring online course quality.

The key areas with the highest number of student concerns (for example, around communication standards, faculty engagement, etc.) were directly linked to areas where they would have been considered 'deficient' or 'developing' on the OLC Quality Scorecard.  From these results, we identified critical topics for faculty PD and resource development for future online programming.


Hackett, A., & Strickland, K. (2018). Using the framework approach to analyse qualitative data: a worked example. Nurse Researcher, 26. doi:10.7748/nr.2018.e1580