Joyce He
I interned with the Smart Primer project led by Professor James Landy, Professor Emma Brunskill and Professor Roy Pea. Inspired by Neal Stephenson’s The Diamond Age, Smart Primer is a tablet-based intelligent tutoring system for kids that leverages compelling narratives, intelligent tutoring chatbots, real-world activities, and a child’s physical and educational context. My role was to assist the project with my knowledge in education and social science.
My main work in the spring quarter was around helping finalize the design decisions, optimizing the learning experience design, measure learning outcomes, and design user testing protocols. In the summer quarter, I helped refine educational tasks, design user testing protocols, and conducted over 35 testings with children aged 8-11.
1. EDUC 229A: Learning Design and Technology Seminar
This quarter we focused on needfinding and formulating a learning problem. The problem space I was exploring was designing learning tools for English as a second language learners on academic writing.
2. EDUC 200B: Introduction to Qualitative Research Methods
I learned research method in A-Level as well as in undergraduate, so I was familiar with this topic. However, I still learned a great deal in this class from both the readings and in-class activities. Denise is an amazing instructor and she has a great teaching team. Writing is a big part of the class and Denise made sure that the teaching team give feedback and allow students to revise their papers based on the feedback. Be aware that this class is group-project heavy and plan your quarter accordingly.
3. EDUC 230: Learning Experience Design
Going through the process of LDT masters’ project, I have to say this project-based class is a great primer for the LDT project. You will get the chance to go through the design process and practice video editing skills (which will come in handy in the summer). Some project-based classes are very disorganized, but not this one. Karin structured this class very well and this is a nice way to ease into learning about design if you don’t have prior experience. For someone who has never gone through the design process, I find this class extremely helpful.
4. EDUC 295: Entrepreneurship and Innovation in Education Technology Seminar
5. EDUC 421: Powerful Ideas for Learning Science and Technology Design, Sociocultural Practice of the Blues
I was lucky that we only had six students in the class and had one great TA and Roy as our professor. The class is discussion based and there was no homework. To meaningfully participate in the class, it is necessary to engage with the readings and there’s a lot of them. It takes a lot of hours but the energy in the room remained one of my best memories here. The only deliverables are a presentation and a paper on the learning journey of a Blues musician of choice. In this class, not only you’ll learn about learning theories, you will “witness” and theorize how learning happens.
6. EDUC 480: Directed Reading with Dr. Bruce McCandliss
For people who have a special interest in neuroscience, make sure to chat with Bruce and keep an eye out for possible directed reading class. You can do directed reading for 1-unit and is a great way to read and learn things that you enjoy and have great discussions with people who share the same interests without taking a heavy course load.
7. OUTDOOR 14: Rock Climbing: Gym to Crag
1. EDUC 229B: Learning Design and Technology Seminar
2&3. EDUC 211&236: Beyond Bits and Atoms - Designing Technological Tools
Many of us took this class and had a great time. This class takes a lot of time. But because it was a lot of fun for me, I never felt that the course load was heavy. All the readings were very interesting and you get to apply what you read into evaluating an educational product. You will do multiple projects throughout the course and all can go into your portfolio. We were also encouraged to submit our project for demo for IDC conference, and three of our projects got in. After getting into IDC, you can apply for GSE conference fund, present your work there and learn from all the great minds there.
4. EDUC 342: Child Development and New Technologies
5. EDUC 423: Introduction to Data Science
This is the first time this class was taught. This class will teach you the basics of data science, the basics of R, machine learning basics and some natural language processing. The content can be very basic if you know how to code and know some machine learning already. However, I find it valuable because you can explore using ML and data science skills for educational dataset. Both Dan and Sanne are great mentors and have done work in the intersection of social science, education and data science.
6. EDUC 480: Directed Reading with Dr. Bruce McCandliss
7. EDUC 100B: East House Seminar: 10 Careers in Education in 10 Weeks
8. PE 7: Core Training
1. EDUC 229C: Learning Design and Technology Seminar
2. EDUC 391: Engineering Education and Online Learning
Despite the title, I find the materials and learning content more about instructional design than anything else. One technique I learned from this class is class Cognitive Task Analysis and I wish I’ve learned it sooner. This class also really pushed me to think about assessment and how to design assessment in an online learning environment. It pushed me so hard that for weeks, assessment was the only thing I had in my mind when I was free. Other good things about the class are that the readings are interesting and it has a diverse teaching team, with people experienced in online learning and game design. The instructor Petr is an LDT alumnus and LSTD Ph.D. candidate and is very knowledgeable about learning analytics. This class is a great opportunity to take your LDT project further. However, be aware and establish expectations for yourself before proposing your LDT project ideas for group project selection.
3. CS 377: Designing Solutions to Global Grand Challenges
Ironically, with a strong intention to learn and build UI/UX skills, this is the first and only HCI class I’ve taken here. I was lucky that I ended up in a team with an education Ph.D. (who happened to be my mentor) and two amazing CS masters student, got to do a language learning project, and had a great time. The class theme of this year was Human-Centered AI, which is a topic I deeply interested in. However, I don’t recommend taking this class without taking CS 147 or CS 247 (my TA said that in CS 247 you learn the same things as in CS 147 and it’s less work). You would dive into your project right away, and the course does assume you know all the basics already. There were limited lecturing and almost every week there’s a presentation. It takes A LOT OF TIME and it’s A LOT OF PRESSURE. I got by by going to TA office hours asking all the basic questions and learning from my teammates. Thanks to the LDT seminars and qualitative research class, I was able to contribute my UX skills to my team.
4. ME 110: Design Sketching
5. PSYC 223B: Topics Neurodiversity: Design Thinking Approaches
I have a deep interest in neurodiversity and universal design for learning. The reason I’m bringing this up is to encourage y’all to take classes from other disciplines. How I found out about this class? I just typed “universal design for learning” in the course catalog and there it was. All the instructors are deeply passionate about this topic and are all experts in the field. The class projects were all directly addressing the current pressing needs of neurodiverse individuals and were deeply meaningful. There was a field trip to inclusive playground and panel discussions with neurodiverse individuals as well as online discussions with other researchers in the field. Overall very meaningful experience and a great course to learn more about neurodiversity and UDL.
6. ENGR 311D: Portfolio To Professional
A 1-unit class that provides the resources, structure, and support to help you build an e-portfolio. If you have a unit to spare and don’t have a portfolio yet, please take this class to make your summer easier. A portfolio is actually a requirement for LDT.
7. ENGR 311B: Designing the Professional
I’ve read the book Designing Your Life (based on this course) and still find this class incredibly meaningful. The instructors are amazing and the homework is fun and meaningful. The class meeting time is more like a fun time where you get to chat with your peers. It also promotes thinking, reflection and life planning. If you’re like me who from time to time find herself at lost, this is a great class to help you find your north star.
1. EDUC 229D: Learning Design and Technology Seminar
2. PSYCH 149S: Vertical Neuroscience: How the Brain Enables Climbing
It happens sometimes. If you just search the keywords that get you excited, you might just find the perfect class for you. #climbing #neuroscience
Together with Tianxing Ma, Elena Semeyko and Diego Sierra, we are the Growing Learning Analytics and Design (GLAD) group, generously funded by the GSE Dean’s Collaborative Learning Fund.
We created this student group, Growing Learning Analytics and Design, to bridge the gaps between academia and industry that we observed in the field of Learning Analytics (LA) and Educational Data Mining (EDM). We successfully planned five events open to the GSE community and held biweekly internal team meetings, where we discussed our learnings in the field of LA and EDM. In addition, as a team, we interviewed experts in this field and attended relevant events, such as the 2019 Bay Area Learning Analytics Network (BayLAN) Conference and Lytics Lab meetings.
In this past year, we have gained numerous insights from these events and group discussions. First, through our high participation rate, we learned that many students are interested in learning more about LA and EDM. Second, we learned there are different frameworks both industry and academy are developing for building data-enriched learning products. Third, while we observed the differences between various stakeholders in their approach to learning analytics, we also saw a promising future if practitioners, industry and academy align their visions and join efforts to build effective learning experiences.
Below are specific examples of these insights that fall under the three main themes mentioned above:
We learned there can be effective partnerships between school districts and industry. For example, the collaboration between Microsoft and Fresno Unified School District empowered the district to reflect and improve on their approaches to learning and helped Microsoft build more relevant products. How can we create more effective partnerships?
We learned that educational data infrastructure shares similarities and challenges with the other industries. For instance, like the healthcare industry, education involves multiple stakeholders who are generating and interacting with data points but who may not be aligned in the vision of how to use and interpret this data. How can we learn from other industries about aligning stakeholders?
We also observed companies are starting to measure more abstract concepts, like “digital collaboration.” By defining what collaboration means and how it is measured, the research conducted by industry has significant impact on the teaching and organizational practices within schools. How can academia join the conversation around rapidly changing technologies?
We learned that researchers at Stanford have come up with a framework to design learning analytics: by aligning learning philosophies, assessments, and outcomes in scalable technology systems. Through a workshop, we learned by doing and felt for ourselves the biggest challenge of learning analytics through designing a system to capture and measure learning for a simplified learning task (teaching the concept of compound interest). How can we choose the appropriate machine measurable learning outcomes that can reliably measure learning without oversimplifying human learning and losing the theoretical/philosophical ground?
We learned from the founder of Gradescope a rubric for developing AI products, framed in a way that people without a technology background can also understand and use. For example, a sustainable and high-quality product often has access to an initial data moat that is exclusive and already labeled and monitors prediction from the models to continuously improve the model, potentially even with the help of its users. How can we build learning products that are scalable and sustainable?
We learned from VIPKID that some companies are currently measuring learning through knowledge assessments, but also student engagement. We were surprised to realize the extent to which the engagement measure was critical for their business model, and therefore was a proxy for student learning as well as teacher assessment. For instance, when student engagement (face recognition and emotions) decreases, a teacher is brought to review the quality of the learning. How can we tell whether engagement is a good proxy for learning?
We also learned from the corporate training perspective. For example, at Mckinsey, they switched their training model from performance management to development management. Moreover, we learned an average employee receives an average of 36 hours of professional development per year. In comparison, public school teachers in the US only receives eight hours per year (Professional Development Day). How can we bring these corporate strategies into K12 learning?
Finally, we realized a group of GSE students created LAMAS (Learning Assessment Measurement and Analytics at Stanford) during spring quarter (Contact person: Paulina Julia Biernacki). This group demonstrates the increasing interest of the GSE community in this topic, as well as the possibility to give continuity to our efforts of bridging the gap between academy and industry.
