When I visited Mumbai for LaTICE 2016, I mentioned meeting Yogendra Pal. I was asked to be a reader for his thesis, which I found fascinating. I’m pleased to report that he has now graduated and his thesis, A Framework for Scaffolding to Teach Vernacular Medium Learners, is available here: https://www.cse.iitb.ac.in/~sri/students/#yogendra.
I learned a lot from Yogendra’s thesis, like what “vernacular medium learners” means. Here’s the problem that he’s facing (and that Yogendra faced as a student). Students go through primary and secondary school learning in one language (Hindi, in Yogendra’s personal case and in his thesis), and then come to University to study Computer Science. Do you teach them (what Yogendra calls “Medium of Instruction” or MoI) in English, or in Hindi? Note that English is pervasive in Computer Science, e.g., almost all our programming languages use English keywords.
Here’s Yogendra’s bottomline finding: “We find that self-paced video-based environment is more suitable for vernacular medium students than a classroom environment if English-only MoI are used.” Yogendra uses a design-based research methodology. He measures the students, tries something based on his current hypothesis, then measures them again. He compares what he thought would happen to what he saw, and revises his hypothesis — and then iterate. Some of the scaffolds he tested may seem obvious (like using a slower pace), but a strength of the thesis is that he develops rationale for each of his changes and tests them. Eventually, he came to this surprising (to me) and interesting result: It’s better to teach with Hindi in the classroom, and in English when students are learning from self-paced videos.
The stories at the beginning of the thesis are insightful and moving. I hadn’t realized what a handicap it is to be learning English in a class that uses English. It’s obvious that the learners would be struggling with the language. What I hadn’t realized was how hard it is to raise your hand and ask questions. Maybe you have a question just because you don’t know the language. Maybe you’ll expose yourself to ridicule because you’ll post the question wrong.
Yogendra describes solutions that the Hindi-speaking students tried, and where the solutions didn’t work. The Hindi-speaking students used English-to-English dictionaries. They didn’t want English-Hindi dictionaries, because they wanted to become fluent in English, but they needed help with the complicated (especially technical) words. They tried using online videos for additional explanations of concepts, but most of those were made by American or British speakers. When you’re still learning English, switching from an Indian accent to another accent is a barrier to understanding.
The middle chapters are a detailed description of Yogendra’s attempts to scaffold student learning. He tried to teach in all-Hindi but some English technical terms like “execute” don’t have a direct translation in Hindi. He selected other Hindi words to represent the technical terms, but the words he selected as the Hindi translation were unusual and not well-known to the students. Perhaps the most compelling insight for me in these chapters was how important it was to both the students and the teachers that the students learn English — even when the Hindi materials were measurably better for learning in some conditions.
In the end, he found that Hindi language screencasts led to better learning (statistically significantly) when the learners (who had received primary and secondary school instruction in Hindi) were in a classroom, but that the English language screencasts led to better learning (again, statistically significantly) when the learners were watching the screencasts self-paced. When the students are self-paced, they can rewind and re-watch things that are confusing, so it’s okay to struggle with the English. In the classroom, the lecture just goes on by. It works best if it’s in Hindi for the students who learned in Hindi in school.
Yogendra tells a convincing story. It’s an interesting question of how these lessons transfer to other contexts. For example, what are the issues for Spanish-speaking students learning CS in the United States? In a general form, can we use the lessons from this thesis to make CS learning accessible to more ESL (English as a Second Language) learners?
I didn’t realize that Computing at School has their own YouTube channel: https://www.youtube.com/c/computingatschooltv
This episode is particularly relevant for this blog — Sue Sentence talking about computing education research: https://www.youtube.com/watch?v=T-NaxSaXtRA
Some of the articles mentioned by Sue (from Miles Berry on the CAS site):
- Lister, R., 2011. Concrete and other neo-Piagetian forms of reasoning in the novice programmer. In Proceedings of the Thirteenth Australasian Computing Education Conference-Volume 114 (pp. 9-18). Australian Computer Society, Inc.
- Cutts, Q., Cutts, E., Draper, S., O’Donnell, P. and Saffrey, P., 2010. Manipulating mindset to positively influence introductory programming performance. In Proceedings of the 41st ACM technical symposium on Computer science education (pp. 431-435). ACM.
- Sorva, J., 2013. Notional machines and introductory programming education. ACM Transactions on Computing Education, 13(2), p.8.
- Zingaro, D. and Porter. L., 2015. Tracking Student Learning from Class to Exam using Isomorphic Questions. In Proceedings of the 46th ACM Technical Symposium on Computer Science Education (SIGCSE ‘15). ACM, New York, NY, USA, 356-361
- Werner, L., & Denning, J. (2009). Pair programming in middle school: What does it look like?. Journal of Research on Technology in Education, 42(1), 29-49
- Price, T.W. and Barnes, T., 2015. Comparing Textual and Block Interfaces in a Novice Programming Environment. In Proceedings of the eleventh annual International Conference on International Computing Education Research (pp. 91-99). ACM.
- Weintrop, D. and Wilensky, U., 2015. To block or not to block, that is the question: students’ perceptions of blocks-based programming. In Proceedings of the 14th International Conference on Interaction Design and Children (pp. 199-208). ACM.
- Margulieux, L. E., Catrambone, R., & Guzdial, M. (2013). Subgoal labeled worked examples improve K-12 teacher performance in computer programming training. In Proceedings of the 35th Annual Conference of the Cognitive Science Society (pp. 978-983).
- Kafai, Y.B. and Vasudevan, V., 2015. Constructionist Gaming Beyond the Screen: Middle School Students’ Crafting and Computing of Touchpads, Board Games, and Controllers. In Proceedings of the Workshop in Primary and Secondary Computing Education (pp. 49-54). ACM.
- Sentance, S. and Csizmadia, A., 2016. Computing in the curriculum: Challenges and strategies from a teacher’s perspective. Education and Information Technologies, pp.1-27.
From Lauren Wilcox:
Betsy DiSalvo, Dick Henneman and I have designed a survey about a topic that is near and dear to us as HCI faculty: topics, learning goals, and learning activities in HCI classrooms!
We hope to do an annual “pulse” of HCI instructors across the globe.
We are hoping that you can take the survey, and also please share with your colleagues who teach HCI-related classes.
Preview ICER 2016: Ebooks Design-Based Research and Replications in Assessment and Cognitive Load Studies
The International Computing Education Research (ICER) Conference 2016 is September 8-12 in Melbourne, Australia (see website here). There were 102 papers submitted, and 26 papers accepted for a 25% acceptance rate. Georgia Tech computing education researchers are justifiably proud — we submitted three papers to ICER 2016, and we had three acceptances. We’re over 10% of all papers at ICER 2016.
One of the papers extends the ebook work that I’ve reported on here (see here where we made them available and our paper on usability and usage from WiPSCE 2015). Identifying Design Principles for CS Teacher Ebooks through Design-Based Research (click on the title to get to the ACM DL page) by Barbara Ericson, Kantwon Rogers, Miranda Parker, Briana Morrison, and I use a Design-Based Research perspective on our ebooks work. We describe our theory for the ebooks, then describe the iterations of what we designed, what happened when we deployed (data-driven), and how we then re-designed.
Two of our papers are replication studies — so grateful to the ICER reviewers and communities for seeing the value of replication studies. The first is Replication, Validation, and Use of a Language Independent CS1 Knowledge Assessment by Miranda Parker, me, and Shelly Engleman. This is Miranda’s paper expanding on her SIGCSE 2016 poster introducing the SCS1 validated and language-independent measure of CS1 knowledge. The paper does a great survey of validated measures of learning, explains her process, and then presents what one can and can’t claim with a validated instrument.
The second is Learning Loops: A Replication Study Illuminates Impact of HS Courses by Briana Morrison, Adrienne Decker, and Lauren Margulieux. Briana and Lauren have both now left Georgia Tech, but they were still here when they did this paper, so we’re claiming them. Readers of this blog may recall Briana and Lauren’s confusing results from SIGCSE 2016 result that suggest that cognitive load in CS textual programming is so high that it blows away our experimental instructional treatments. Was that an aberration? With Adrienne Decker’s help (and student participants), they replicated the study. I’ll give away the bottom line: It wasn’t an aberration. One new finding is that students who did not have high school CS classes caught up with those who did in the experiment, with respect to understanding loops
We’re sending three of our Human-Centered Computing PhD students to the ICER 2016 Doctoral Consortium. These folks will be in the DC on Sept 8, and will present posters to the conference on Sept 9 afternoon.
- Barbara Ericson will be presenting her results with Dynamically Adaptive Parsons Problems. I’ve seen some of the pilot study results from this summer, and they’re fascinating.
- Amber Solomon is just starting her second year working with me. She did the evaluation on the AR Design Studio classroom. She (and I) is fascinated by Steve Cooper’s results from ICER 2015 where spatial reasoning training influenced CS performance and reduced SES differences. She’s been doing a study on CS grades, SES, and spatial reasoning in a non-majors class. She’ll be presenting on The Role of Spatial Reasoning in Learning Computer Science.
- Kayla DesPortes works with my colleague Betsy DiSalvo on the learning that happens in MakerSpaces. She’s designing new kinds of physical interfaces to reduce cognitive load and improve learning when working with electronics, which she’ll be talking about at her poster: Learning and Collaboration in Physical Computing.
Why ‘U.S. News’ should rank colleges and universities according to diversity: Essay from Dean Gary May #CSforAll
Georgia Tech’s Dean of Engineering Gary May was one of the advisors on “Georgia Computes!” He makes a terrific point in his essay linked below. Want broadened participation in computing (BPC)? CS for All? Make diversity count — and rankings are what “counts” in higher education today.
U.S. News & World Report, that heavyweight of the college rankings game, recently hosted a conference focused partially on diversity in higher education. I did an interview for the publication prior to the forum and spoke on a panel at the event.I was happy to do it. As dean of one of the country’s most diverse engineering schools, I am particularly invested in these issues. My panel focused on how to help women and underrepresented minority students succeed in STEM fields, and I’m grateful to U.S. News for leading the discussion.But the publication, for all its noble intentions, could do more to follow through where it counts. Diversity is currently given no weight in the magazine’s primary university and disciplinary rankings, and it’s time for that to change. As U.S. News goes, so goes higher education.
Malcolm Gladwell’s new podcast, Revisionist History, recently included a mini-series about the inequities in society that higher education perpetuates. Higher education is a necessity for a middle class life in today’s US, but not everyone gets access to higher education, which means that the economic divide grows larger. We in higher education (an according to Richard Tapia in his foreword to Stuck in the Shallow End, we in computer science explicitly) may be playing a role in widening the economic divide. David Brooks wrote about these inequities in 2005, in his NYTimes column, titled “The Education Gap“:
We once had a society stratified by bloodlines, in which the Protestant Establishment was in one class, immigrants were in another and African-Americans were in another. Now we live in a society stratified by education. In many ways this system is more fair, but as the information economy matures, we are learning it comes with its own brutal barriers to opportunity and ascent.
Gladwell has written about higher education before. In David and Goliath: Underdogs, misfits, and the art of battling giants, he told the story of Caroline Sacks who loved science since she was a little girl. When she applied to college, she was accepted into both University of Maryland and Brown University. She chose Brown for its greater prestige. Unfortunately, that prestige came with a much more competitive peer set. Caroline compared herself to them, and found herself wanting. She dropped out of science. Gladwell suggests that, if she’d gone to Maryland, she might have persisted in science because she would have fared better in the relative comparison.
Gladwell’s three podcasts address who gets in to higher education, how we pay for financial aid for poorer students, and how we support institutions that serve poorer students.
In Carlos doesn’t remember, Gladwell considers whether there are poorer students who have the academic ability to succeed but aren’t applying to colleges. Ivy League schools are willing to offer an all-expenses-paid scholarship to qualified students whose family income is below a certain level, but they award few of those scholarships. The claim is that there are just few of those smart-enough-but-poor students. Economists Avery and Hoxby explored that question and found that there are more than 35,000 students in the United States who meet the Ivy League criteria (see paper here). So why aren’t they applying for those prestigious scholarships?
Gladwell presents a case study of Carlos, a bright student who gets picked up by a program aimed at helping students like him get access to high-quality academic opportunities. Gladwell highlights the range of issues that keep students like Carlos from finding, getting into, and attending higher education opportunities. He provides evidence that Avery and Hoxby dramatically underestimate the high-achieving poor student, e.g., Avery and Hoxby identified some students using eighth grade exam scores. Many of the high-achieving poor students drop out before eighth grade.
As an education researcher, I’m recommending this podcast to my graduate students. The podcast exemplifies why it’s so difficult to do interview-based research. The title of the episode comes from Carlos’s frequent memory lapses in the interview. When asked why he didn’t mention the time he and his sister were taken away from their mother and placed in foster care, Carlos says that he doesn’t remember that well. It’s hard to believe that a student this smart forgets something so momentous in his life. Part of this is a resilience strategy — Carlos has to get past the bad times in his life to persist. But part of it is a power relationship. Carlos is a smart, poor kid, and Gladwell is an author of international bestsellers. Carlos realizes that it’s in his best interest to make Gladwell happy with him, so he says what he thinks Gladwell wants to hear. Whenever there is a perceived power gap between an interviewee (like Carlos) and an interviewer (Gladwell), we should expect to hear not-quite-the-truth. The interviewee will try to tell the interviewer what he thinks the world-famous author wants to hear — not necessarily what the interviewee actually thinks.
The episode Food Fight contrasts Bowdoin College in Maine and Vassar College in New York. They are similar schools in terms of size and academics, but Bowdoin serves much better food in its cafeterias than Vassar. Vassar made an explicit decision to cut back in its food budget in order to afford more financial aid to its poorer students. Vassar spends almost twice as much as Bowdoin in financial aid, and has a much higher percentage of low-income students than Bowdoin. Vassar is explicit in the trade-offs that they’re making. Gladwell interviews a student who complains about the food quality, but says that she accepts it as the price for having a more diverse student body.
But there’s a tension here. Vassar can only afford that level of financial aid because there is a significant percentage of affluent students who are playing full fare — and those affluent students are exactly the ones for which both Bowdoin and Vassar compete. Vassar can’t balance their budget without those affluent students. They can’t keep providing for the poorer students unless they keep getting their share of the richer students. Here’s where Gladwell starts the theme he continues into the third episode, when he tells his audience, “Never give to Bowdoin!”
The third episode, My Little Hundred Million, starts from Hank Rowan giving $100 million to Glassboro State University in New Jersey. At the time, it was the largest philanthropic gift ever to a higher education institution. Since then there have been others, but all to elite schools. Rowan’s gift made a difference, saving a nearly-bankrupt university that serves students who would never be accepted at the elites. It made a difference in providing access and closing the “Education Gap,” in exactly the way that David Brooks was talking about in 2005. So why are such large gifts going instead to schools like Stanford and Harvard, who don’t play a role in closing that gap? And why do the rich keep giving to the elite institutions? Gladwell continues the refrain from the last episode. Stop giving to Harvard! Stop giving to Stanford!
The most amazing part of the third episode is an interview with Stanford President, John Hennessy. Gladwell prods him to defend why Stanford should get such large gifts. Hennessy talks about the inability of smaller, less elite schools to use the money well. Do they know how to do truly important things with these gifts? It’s as if Hennessy doesn’t understand that simply providing access to poor students is important and not happening. Hennessy is painted by Gladwell as blind to the inequities in the economy and to who gets access to higher education.
I highly recommend all of Revisionist History. In particular, I recommend this three-part mini-series for readers who care about the role that higher education can play in making our world better. Gladwell tells us that higher education has a critical role to play, in terms of accepting a more diverse range of students through our doors. We won’t do much to address the problems by only focusing on the “best and brightest.” As Richard Tapia writes in his foreword to Stuck in the Shallow End, that phrase describes much of what we get wrong in higher education.
“Over the years, I have developed an extreme dislike for the expression ‘the best and the brightest,’ so the authors’ discussion of it in the concluding chapter particularly resonated with me. I have seen extremely talented and creative underrepresented minority undergraduate students aggressively excluded from this distinction. While serving on a National Science review panel years back, I learned that to be included in this category you had to have been doing science by the age of ten. Of course, because of lack of opportunities, few underrepresented minorities qualified.”
Closing the Education Gap requires us to think differently about who we accept into higher education, who we most need to be teaching, and how we pay for it.
White House Call to Action: Incorporating Active STEM Learning Strategies into K-12 and Higher Education
I’m so happy to see this! I’ve received significant pushback on adopting active learning among CS faculty. Maybe a White House call can convince CS higher education faculty to adopt active learning strategies?
Active learning strategies include experiences such as:
- Authentic scientific research or engineering or software design in the classroom to help students understand the practice of science, technology, and engineering and promote deep learning of the subject matter;
- Interactive computer activities to support students’ exposure to trial-and-error and promote deep learning;Discussions to encourage collaboration and idea exchange among students; and
- Writing to generate original ideas and solidify knowledge.
Today, the White House Office of Science and Technology Policy is issuing a call to action to educators in K-12 and higher education, professional development providers, non-profit organizations, Federal agencies, private industry, and members of the public to participate in a nationwide effort to meet the goals of STEM for All through the use of active learning at all grade levels and in higher education.