Chapter 1 May 16–22: Introduction

This chapter contains everything that you need to do for Week 1 of HE-930. The first deadline for this course is Sunday May 22 2022, which is when you should please turn in the assignment in this chapter. Please read and follow the instructions in this chapter carefully and then complete the assignment at the end.

This week, our goals are to…

  1. Evaluate and articulate PA (predictive analytics) research questions that apply to education.

  2. Discuss the purpose of PA in educational contexts.

  3. Respond to examples of the use of PA in health professions education.

  4. Complete the following logistical tasks: a) Double-check that R and RStudio are running on your computer; b) Schedule journal club meetings; c) Schedule synchronous seminar; d) Arrange to watch The Social Dilemma on Netflix.

1.1 Course introduction

Welcome to HE-930! This textbook will guide you through the entire course. Every week, just go to the chapter corresponding to that week and follow the readings, videos, and instructions. Then, complete and submit the assignment in each chapter. That is the basic procedure we will follow in this course each week.

Here are some additional details to help you get started:

  • Please feel free to contact us (the instructors of HE-930) at any time for any reason. You can reach us by e-mail, as explained in the introductory emails that you should have received from us when the course started.

  • In addition to completing each week’s chapter in the course, you are also required to engage in additional activities such as journal clubs, an oral exam, and a final project. These activities are detailed in the Information and Reference chapter of this textbook, in the Learning Activities, Oral Exam, and Final Project sections. That chapter also contains the Calendar for our course, which shows when all of these activities will occur.

  • All discussion post assignments should be submitted to the appropriate discussion forum in the D2L website for our course, which you can access at https://mghinstitute.desire2learn.com/d2l/home/216827. Once you are at the D2L website, click on Communication and then Discussions. Then, click on the discussion corresponding to the week of the course you are working on and submit a response.

  • All data analysis assignments should be submitted to the appropriate dropbox in D2L. To access the dropbox, once you are at the D2L website, click on Assessments and then Assignments. Then, click on the assignment for the week you are working on and upload your work.

Thanks for reading the course information above. Please continue reading below to start working on Week 1 of the course!

1.2 Predictive analytics in education, healthcare, and health professions education

To begin our study of predictive analytics (PA) and machine learning (ML), we will read some scholarship and examples of how PA and ML are used in practice today. We will also watch some videos.

Here are a few notes to keep in mind as you begin:

  1. Most of these readings and videos will be revisited in our ongoing discussions, and especially during Week 3.

  2. In this week’s readings, there may be research methods and algorithms mentioned that you do not yet know about. That is fine. You can shortlist these to ask about or simply focus on the aspects of the predictive methods mentioned that do make sense to you (most importantly, the research questions and their answers).

  3. “Features” are the same as “variables,” meaning columns of data in a data set or spreadsheet.

Required readings about the use of PA and ML in HPEd or similar fields:

Please read the following articles or resources:

  1. Ekowo M, Palmer I. The Promise and Peril of Predictive Analytics in Higher Education: A Landscape Analysis. New America. 2016 Oct. https://eric.ed.gov/?id=ED570869. PDF: https://files.eric.ed.gov/fulltext/ED570869.pdf.

  2. Allen P. Transforming Health Professions Education: Are We There Yet?. The Journal of Continuing Education in Nursing. 2016 Mar 1;47(3):99-100. https://doi.org/10.3928/00220124-20160218-01. MGH Treadwell Library permalink: click here.

  3. Akçapınar G, Altun A, Aşkar P. Using learning analytics to develop early-warning system for at-risk students. International Journal of Educational Technology in Higher Education. 2019 Dec;16(1):1-20. https://doi.org/10.1186/s41239-019-0172-z. PDF: https://educationaltechnologyjournal.springeropen.com/track/pdf/10.1186/s41239-019-0172-z.pdf.

  4. Saqr M, Fors U, Tedre M. How learning analytics can early predict under-achieving students in a blended medical education course. Medical teacher. 2017 Jul 3;39(7):757-67. https://doi.org/10.1080/0142159X.2017.1309376. MGH Treadwell Library permalink: click here.

PDF versions of the readings above can be accessed in our course’s D2L website by clicking on Course Materials followed by Content and then Week 1.

Required introductory videos:

Please watch the following two videos:

Decisive Data. 2018. The Fundamentals of Predictive Analytics - Data Science Wednesday. https://www.youtube.com/watch?v=4y6fUC56KPw. Watch at the YouTube link or embedded below.

Cognitive Class. 2017. Machine Learning vs Statistical Modeling. https://www.youtube.com/watch?v=jaI5aheBOi0. Watch at the YouTube link or embedded below.

Optional (not required) reading:

  1. Arnold KE, Pistilli MD. Course signals at Purdue: Using learning analytics to increase student success. In Proceedings of the 2nd international conference on learning analytics and knowledge 2012 Apr 29 (pp. 267-270). https://doi.org/10.1145/2330601.2330666. PDF: click here.

1.3 Assignment

Now that you have completed this week’s readings and videos, it is time to turn to the assignment below. This week’s assignment includes some logistical tasks to help us get started with the course as well as some substantive tasks that will ask you to synthesize the information from this week’s readings and videos.

The deadline for completing all of the tasks in this assignment is Sunday May 22 2022.

1.3.1 Learn about the course

We begin the assignment with a request for you to read some of the key information about this course:

Task 1: If you have not done so already, please carefully read the Calendar and Learning Activities sections of this textbook’s Information and Reference chapter. (You don’t have to read the other sections right now; you can do it later). After reading these sections, do you have any questions about the course? If so, please email them to both Nicole and Anshul.

1.3.2 Logistical tasks

We now turn to some logistical tasks that we want to accomplish this week, so that the rest of the course can run as smoothly as possible.

Task 2: In Week #3 of our class, we will all participate in an annual tradition in HE-930. In Week #3, there will be no assignment for you to complete. Instead, you will participate in three synchronous seminar sessions on Zoom. To help us decide when to schedule these sessions, please fill out the poll at https://www.when2meet.com/?15674279-Izdfv to let us know when you are available. You are required to fill out this poll. The poll also asks for your availability for the weekends before and after Week 3, in case those end up being times that suit many of us in the class. We will look at the poll responses and then determine timings and durations for our synchronous seminar sessions.

Task 3: Before attending the synchronous seminar sessions in Week 3, you will be required to watch a few videos. One of these videos is called The Social Dilemma and is available on Netflix. If you already have access to Netflix, please check if you are able to view The Social Dilemma (you do not need to watch the whole thing this week; just see if you are able to watch it). If you do not have access to The Social Dilemma on Netflix, please inform Nicole and Anshul right away by email, and we will arrange for you to watch it. This link might take you to the Netflix page for The Social Dilemma: https://www.netflix.com/us/title/81254224. It is from the year 2020 and it runs for 1 hour and 34 minutes (according to its Netflix listing).

Task 4: Double-check that R and RStudio are running correctly on the computer(s) that you plan to use for this course. If you have taken the course HE-902 already, then you should know how to do this. If you have not yet taken the course HE-902, you should have received an email from an instructor with more information about setting up R and RStudio. We would like everyone to have R and RStudio set up and operational on your computer by the deadline for this Week 1 assignment. Please email both Nicole and Anshul with any questions related to this.

Task 5: We want to make sure that you are receiving communications from us related to this course. By the first week of class, you should have received a) one or more emails from us and b) one or more calendar invitations for office hours. If you have not received either of these, please let us know immediately (by emailing us, calling us, including a note in your discussion post, asking your academic advisor, or any other reasonable means).

Task 6: As you can see in our course calendar, there are five weeks in which we are scheduled to have journal club sessions. Each of these journal club meetings will have 2–4 student leaders. Below, each of you are assigned to a week in which you and some classmates will be the leaders.

  • Week of June 13: RA, RA, HL, CZ
  • Week of June 27: SA, SA, RP
  • Week of July 11: MC, HD, LR
  • Week of July 25: JF, NF, RS
  • Week of August 8: SG, FJ, PS

Above, look for your initials (a copy of this list with complete first names was emailed to you as well, which might be easier to read). That is the week in which you are preliminarily assigned to be the journal club leader. You and your co-leaders that week should decide the time at which the journal club meeting is held, and then inform Nicole and Anshul. For example, in the week of July 11, the three leaders are MC, HD, and LR; these three students should confer over email and decide what one-hour time slot is convenient for all of them to lead journal club during or after the week of July 11. They should then tell Nicole and Anshul what time and day they selected.

  • If you are not available to lead journal club in the week assigned above, that is fine. Just email Nicole and Anshul to let us know. We will move you to a different group.
  • If you are not available in any of the weeks above, that is also fine. We can add more journal club meetings and hold them in other weeks as well. This is just a starting point for our planning.

In summary, this is what you should do to complete this task: Email with the other students who were assigned in the same week as you, above. Decide on a one-hour time during that week when you are all available. Email Nicole and Anshul with that time and day. This is the first step for organizing our journal clubs for this summer.

I know that the logistical tasks above might have been tedious to complete. Thanks for your patience and attention to detail. In previous years of this course, these logistics have ended up working out well, so we believe that they will again this year. And of course, we are always open to your feedback for modifications to our plan as long as we can still achieve our learning goals.

1.3.3 Discussion post

Now we can finally turn back to this week’s content related to predictive analytics (PA) and machine learning (ML). Please write responses to the following questions or prompts and submit them in the Week 1 discussion section in D2L.

Task 7: What were the research questions addressed in Ekowo & Palmer 2016 (list two), Akçapınar et al 2019 (list all), and Saqr et al 2017 (list all)?

Task 8: For the Akçapınar et al 2019 study, answer the following questions.

  1. Which predictive methods were used and what is the answer to the research question(s)? Please provide your commentary and reaction to these findings.
  2. What were the limitations of the study?

Task 9: For the Saqr et al 2017 study, answer the following questions:

  1. Which predictive methods were used and what is the answer to the research question(s)? Please provide your commentary and reaction to these findings.
  2. What were the limitations of the study?

Finally, please respond to the following:

Task 10: What questions do you have coming out of this week?

You are welcome (but not yet required) to respond to your classmates’ posts at any time!

You have reached the end of this week’s assignment. Please make sure to submit your responses to all tasks to the appropriate places (emails to each other or Nicole and Anshul in the case of the logistical tasks, and submission to the discussion board in D2L for your discussion post).