Educational Technology 2 Assignments

Welcome to OMS CS6460: Educational Technology!

Welcome! This is the landing page for the Georgia Tech OMS CS6460 class on Educational Technology.

This page provides general information about the course as a whole. If you are interested in information specifically about one particular offering of the course, such as a particular semester’s syllabus, calendar, and assignments, please see Past Semesters section below, or  jump straight to the current semester. This class is built heavily around the course library, a curated archive of publications, articles, projects, biographies, tools, videos, presentations, and original interviews on a number of topics in Educational Technology.

Welcome to EdTech!

Welcome to the OMS offering of CS6460: Educational Technology! I’m excited to bring this class to you in the OMS program. As OMS students, you’re actively experiencing educational technology in action, and that uniquely suits you for both learning about it and contributing back to it. This course will be something of an experiment in the OMS program: whereas most classes are built on a foundation of pre-recorded video lectures, this class will have very few of these. Instead, this class is an experiment in administering a discussion-oriented graduate class in an asynchronous online environment. Thus, this class is as much an experiment in educational technology as it is a class on educational technology.

Readiness Questions

In order to succeed in this class, you should be able to answer yes to the following questions:

  • Have you already fulfilled the foundational requirement for the program?
  • Are you comfortable with writing several essays throughout the course of the class, including personal reflections, article responses, project proposals, and project reports?
  • Are you comfortable with a class that requires significant participation via forum interactions and peer-to-peer feedback opportunities?
  • Are you comfortable working in a group; or, alternatively, are you comfortable taking on a significantly-sized project on your own?
  • Are you passionate about education, and ideally, do you already have some preliminary ideas regarding what tools you might like to build or questions you might like to research as part of this class?
  • Are you comfortable with a class built on large, open-ended, student-driven projects rather than smaller, more narrowly-defined assignments and exams?

Note that prior experience with EdTech is not required beyond your prior OMS coursework. Note also that because they project is very open-ended, you’ll be able to define a project that is realistic within your technical qualifications. So, no specific programming knowledge is required. If you choose more of a research-oriented track, you may not need to do any programming at all.

Course Description

This class is simultaneously an introductory course about educational technology and an advanced, project-oriented class on designing or researching technology’s intersection with education. As such, the course provides information about a large number of topics within educational technology, including pedagogical strategies, research methodologies, current tools, open problems, and broader issues. The scope of the material provided goes beyond what any one person could reasonably learn in a semester. Instead, you will select those areas that appeal to you or that support your ultimate project ideas. For example, if you’re interested in research, you may focus on the applicable research methodologies to your chosen area of investigation, relevant pedagogical strategies or theories, and the current state-of-the-art within that community.  If you’re interested in design, you may focus on the relevant pedagogical strategies or theories for your chosen domain, the current popular tools within that domain, and open problems that need to be addressed.

This class is built on a number of pedagogical strategies, including project-based learning, authenticity, and apprenticeship. The ultimate goal, supported by these strategies, is that through this class you will make an actual contribution to the field of educational research, and start a project that could be continued even after the semester is over through academic publications, ongoing research programmes, start-up businesses, or deployment within the OMSCS program.

Learning Goals

A learning goal is what you should know by the end of the class. The broad learning goal for this class is that, by the end of the class, you will have the requisite knowledge to make a real contribution to the Educational Technology field.

Even established experts in the field do not know everything, however, and neither will you. Instead, by the end of this class, you will have sufficient knowledge to contribute to the field in some way, though not every way. This means the learning goal of the class is determined in part by your own goals in taking this class:

  • Are you interested in understanding how technology can help education more theoretically? Then your learning goals would include knowledge of research methodologies, promising pedagogical strategies, and current theories in the community.
  • Are you interested in designing technologies that can help learners learn better? Then your learning goals would include knowledge of pedagogical strategies, current state-of-the-art tools, and the open problems in education and technology.
  • Are you interested in evaluating existing technologies? Then your learning goals would include knowledge of research methodologies in user testing, current state-of-the-art tools, and broader issues surrounding the impact of such tools.
  • Are you interested in contributing to the education enterprise more broadly, even if it isn’t at the point of learning? Then your learning goals would include knowledge of the current problems in the field, broader issues surrounding the use of tools in supporting education, and the present tools that address those problems.

By achieving these learning goals, you will end the class with the knowledge necessary to contribute to the portion of educational technology in which you are most interested.

Learning Outcome

If a learning goal is something you should know by the end of the course, then a learning outcome is something demonstrable you should be able to do. The learning goals were all partially dependent on your area of interest within educational technology, and thus, so also are the outcomes. The learning goals included the knowledge necessary to perform certain tasks, and thus, the learning outcomes are the actual performance of those tasks.

  • Are you interested in understanding how technology can help education more theoretically? Then your learning outcome is the ability to design and conduct research or experiments in educational technology, to analyze the results, to report the results, and to position the results in the context of a broader research community.
  • Are you interested in designing technologies that can help learners learn better? Then your learning outcome is the ability to design pedagogically sound tools for learning, to position those tools in the broader EdTech industry, and to present a case for the value of those tools.
  • Are you interested in evaluating existing technologies? Then your learning outcome is the ability to design and conduct experiments on existing technologies, to gather and analyze participant feedback on those technologies, and to recommend changes that are both pedagogically sound and supported by research.
  • Are you interested in contributing to the education enterprise more broadly, even if it isn’t at the point of learning? Then your learning outcome is the ability to design tools that support education in other areas besides teaching, to analyze the broader impacts of those tools, and to analyze the effectiveness of those tools compared to existing methods for addressing those problems.

By achieving these learning outcomes, you will end the class not only with the knowledge necessary to contribute, but also with experience in actually contributing.

Learning Assessment

If learning goals are what you should know, and learning outcomes are what you should be able to do, then learning assessments are how we evaluate whether you know what you should know and can do what you should be able to do. The learning goals and outcomes both connected to contributing to educational technology, and so the learning assessments in this course will be based on the extent to which you actually contribute to educational technology.

This contribution will take on different forms depending on your interests. It may be a research contribution to some academic community. It may be a tool to support learning in classrooms or non-traditional learning environments. It may be a technology to support a portion of the broader education enterprise, such as admissions or academic integrity. It may be a report on the effectiveness of certain existing tools or strategies in learning.

The ultimate goal is that the project you choose to take on in this class won’t end with the end of the semester; we hope your project continues on and leads to publications, ongoing research, a start-up business, or a tool we can continue to use here in the program. In order to maximize the chances of that happening, the assessments will include steps to get your work ready for publication or for a start-up pitch.

Learning Strategies

A number of learning strategies are employed to try to connect with these learning goals, outcomes, and assessments. Because this is a class on education, these strategies are also demonstrations of portions of the course content. Some of the learning strategies you will see are:

  • Project-Based Learning. The entire class is built around a large project, defined by you, that itself should represent an authentic contribution to the EdTech community.
  • Authenticity. The goal of this course is to make a real contribution to the field. Success in the course won’t just mean mastering some concepts in a controlled classroom environment; it will be creating a real, authentic contribution to educational technology.
  • Apprenticeship. While TAs in most classes focus largely on grading, the primary function of TAs in this class is mentorship. You’ll interact closely with your mentor to develop your understanding, propose and scope your project idea, and deliver something valuable by the end of the semester.

Additional pedagogical strategies we’ll leverage heavily in this class include learning by doing, learning by teaching, learning by reflection, collaborative learning, communities of practice, and more.

Course Structure

One of the significant motivations behind creating this course was the number of students that expressed interest in experiencing research as part of their Master’s degree. To help facilitate this, we have drawn considerable inspiration in structuring this class from the ultimate research experience: getting a PhD.

Phase I: Acquiring Knowledge

The course starts with a few weeks of intensive study into the portion of educational technology in which you are most interested. You will use the library we provide as a starting point, but ultimately we hope and expect your research will take you outside the resources we have provided. This is the first learning goal in becoming a researcher: learning to gather and synthesize information from a community. During this time, you will write a number of reflective assignments both to reflect on what you’re learning and to share your growing understanding with your mentor and classmates. This is analogous to the first two years of a PhD, where new PhD students typically spend most of their time in extensive literature review to become experts in their field. This phase will last approximately four weeks.

Phase II: Demonstrating Mastery

Next, you will answer a targeted question about your areas of interest. This question will evaluate how ready you are to contribute to the field you have chosen. You will be asked a question that will require knowledge of your community or area of interest, the ability to reason about that community, and a perspective on how you might contribute to that community. This is the second learning goal in becoming a researcher: to understand a community well enough to participate in its conversations. This is analogous to the qualifier test of a PhD, an intense test at the end of the second year assessing a PhD student’s expertise in the community. This phase will last approximately one week.

Phase III: Proposing Projects

Then, you will propose your project. Using what you have learned from the community, you will propose something that will be a real contribution or expansion on the community’s current state of the art. As part of this proposal, you will describe the tool in context of the existing community, provide a statement of expected work, and detail a plan for achieving that work. This is the third learning goal in becoming a researcher: to know how to structure research or design such that it will ultimately lead to a useful contribution. This is analogous to the proposal phase of a PhD, where a PhD student will compile a detailed document describing what they will do for their ultimate dissertation. This phase will last approximately two weeks.

Phase IV: Executing Projects

Then, you will do your project. You’ll execute the plan of work that you stated in your proposal, ultimately creating a deliverable project. This is the fourth learning goal in becoming a researcher: to actually be able to execute the implementation of a tool or completion of some research and analysis. During this time, you will regularly share information and progress with your mentor to monitor for obstacles and ensure you stay on the path to completing the work by the completion date. This is analogous to the dissertation research phase of a PhD, where a PhD student actually performs the work they agreed to do in their proposal. This phase will last approximately nine weeks.

Phase V: Delivering Projects

Finally, you will actually deliver the results of your project. You’ll compile the tool you designed or the research you performed and share them with your mentor and the class as a whole. This is the fifth learning goal in becoming a researcher: to be able to disseminate the results of your work. This is analogous to the dissertation defense phase of a PhD, where a PhD student compiles their work into a dissertation and defends it in a dissertation defense presentation. As such, this will include three deliverables: the project itself (e.g. the tools, research results, designs, or other artifacts produced for the project), a paper (analogous to a dissertation), and a presentation (analogous to the dissertation defense. This phase will last approximately one week.

At the conclusion of this class structure, you will have a completed project, a publication-ready paper for submission to the most relevant conference or journal (if you so choose), and a presentation for sharing your work with classmates and other potentially interested parties. Note that although this course is structured around a research activity (that is, getting a PhD), we anticipate that this structure will be useful to those preferring to go into business or industry as well. The overall structure of gaining knowledge of a community, proposing a contribution to it, and delivering that contribution is fairly universal; here, we’ve merely borrowed the milestones and terminology from academia, but this process is similarly applicable to industry.

Semesters

The above information is general to the OMS CS6460 class. For information about specific semesters, such as project information, calendars, and grading criteria, please select the specific semester below:

Time:TTh 1:30-3:00
Location:College of Computing Building (CCB) 101
Instructor:Amy Bruckman
Office:CCB 255
Email:asb@cc.gatech.edu
(Email is best way to reach me.)
Office Hours:Find me after class or email for an appointment
Teaching Assistant: Jim Hudson
TA Email:jhudson@cc.gatech.edu
Coweb:http://swiki.cc.gatech.edu:8080/cs4660
Newsgroup:git.cc.class.cs4660

Texts:

  • How People Learn: Brain, Mind, Experience, and School by John Bransford, Ann L. Brown, Rodney R. Cocking, et al. Washington: National Academy Press, 1999.
    (On back order at the Georgia Tech bookstore. Used copies available at Engineer's bookstore. To order online, visit Best Book Buys, or click here to buy from Amazon books with the profit from the sale going to buy pizza for students in this and other classes.)
  • Course pack (Available from the Georgia Tech bookstore.)
  • Articles online


Prerequisite

There are no prereqs. Students from all departments are welcome.

CS majors should know that the class requires more reading and writing than most CS classes. It's time consuming, but a nice mental break from programming and problem sets. You'll get a chance to practice your writing skills, which are one key to your future career success regardless of what career you chose.


Focus of the Course

In this class, we will begin by studying theories of learning. Next, we'll explore how those theories lead you to design different kinds of educational software and hardware. A variety of different approaches to educational technology will be presented. In the software analysis assignment in the first half of the semester, you'll identify the theory of learning behind a particular commercial or research example of educational technology. In the design assignments in the second half of the course, you'll propose designs for educational technology based on two different approaches to learning.

Ethical issues in appropriate use of technology in educational settings will also be discussed.


Grading

Your grade will be based on these assignments:
  1. Personal Learning Experience (5%)
  2. Software Analysis (10%)
  3. Midterm (20%)
  4. Design Assignment (30%)
  5. Final (25%)
  6. Class Participation (10%)

Suggested assignment lengths are approximate. Some people will do a good job in less and some will require many more pages. Please don't play games with the margins or fonts to try to make it come out a certain length--no one is counting. Don't worry about the page count--just make sure that you've completed the assignment well. Please remember to double space papers so we can write comments.


Computing Resources

If you registered for the class and you already have a CoC account, you have been given access to College of Computing machine clusters (if you didn't have access already). If you register late, you should be added later automatically. If not, mail help@cc asking to be given access.

If you need a CoC account, you can get a request form in front of CCB 213. Complete the form and return it there. Booklets on available CoC computing resources are available outside of room CCB 140.


Course Outline

All readings are subject to change.
  • (8/19) Introduction
  • (8/21) Learning--From Speculation to Science

    Reading:

    • How People Learn - Chapter 1
  • (8/26) Learner-Centered Design

    Due: short essay on your educational experience

    Reading:

    • Soloway, E., Guzdial, M., & Hay, K. E. (1994). Learner-Centered Design: The Challenge for HCI in the 21st Century. Interactions, 1(2), 36-48. (Course Pack)
  • (8/28) How Experts Differ from Novices

    Reading:

    • How People Learn - Chapter 2
  • (9/2) Technology to Support Learning

    Reading:

    • How People Learn - Chapter 9
  • (9/4) Cognitive Apprenticeship

    Reading:

    • Collins, A., Brown, J. S., & Newman, S. E. (1989). Cognitive apprenticeship: Teaching the craft of reading, writing, and mathematics. In L. B. Resnick (Ed.), Knowing, Learning, and Instruction: Essays in Honor of Robert Glaser (pp. 453-494). Hillsdale, NJ: Lawrence Erlbaum and Associates. (Course Pack)
  • (9/9) Transfer & Factors that Affect Learning

    Reading:

    • How People Learn - Chapter 3

    Surfing Assignment:

  • (9/11) Cognitive Tutors

    Reading:

    • Anderson, J. R., Corbett, A. T., Koedinger, K. R., & Pelletier, R. (1995). Cognitive Tutors: Lessons Learned. Journal of the Learning Sciences, 4(2), 167-208. (Online Reserve)

    Software:

  • (9/16) The Role of Computers in the Classroom

    Reading:

    • Cuban, L. (2001). Oversold and Underused: Computers in the Classroom (pp. 152-159, 167-170, 176-197). Cambridge: Harvard University Press. (Handout)
  • (9/18) Problem and Project Based Learning

    Reading:

    • Barron, B. J. S., Schwartz, D. L., Vye, N. J., Moore, A., Petrosino, A., Zech, L., Bransford, J. D., & CTGV. (1998). Doing with Understanding: Lessons from Research on Problem- and Project-based Learning. Journal of the Learning Sciences, 7(3&4), 271-310. (Online Reserve)
  • (9/23) Constructionism

    Reading:

  • (9/25) How Children Learn

    Reading:

    • How People Learn - Chapter 4
  • (9/30) Design of Learning Environments

    Reading:

    • How People Learn - Chapter 6
  • (10/2) Software Demo Day

    Due:

  • (10/7) Software Demo Day, Part 2
  • (10/9) Midterm
  • (10/14) School Holiday - No Class
  • (10/16) Learning Through Programming

    Reading:

    • Harel, I., & Papert, S. (1990). Software Design as a Learning Environment. Interactive Learning Environments, 1(1), 1-32. (Course Pack)
  • (10/21) Designing Novice Programming Languages

    Reading:

    • diSessa, A. A., & Abelson, H. (1986). Boxer: A Reconstructible Computational Medium. Communications of the ACM, 29(9), 859-868. (Course Pack)
  • (10/23) Designing Construction Kits

    Reading:

  • (10/28) Epistemological Pluralism

    Reading:

  • (10/30) Educational Uses of the Internet

    Reading:

    Due:

  • (11/4) Simulation and Modeling

    Readings:

  • (11/6) Design Experiments

    Readings:

    • Brown, A. L. (1992). Design Experiments: Theoretical and Methodological Challenges in Creating Complex Interventions in Classroom Settings. The Journal of the Learning Sciences, 2(2), 141-178. (Online Reserves)
  • (11/11) Personal Identity and Learning

    Readings:

    • Turkle, S. (1984). Adolescence and Identity: Finding Yourself in the Machine, The Second Self: Computers and the Human Spirit. New York: Simon and Schuster. (Course Pack)
  • (11/13) Power

    Readings:

    • Kohl, H. (1994). I Won't Learn From You, "I Won't Learn from You" and Other Thoughts on Creative Maladjustment (pp. 1-32). New York: The New Press. (Course Pack - p. 1-10, 32)
  • (11/18) In-Class Presentations

    Due:

    (11/20) In-Class Presentations
  • (11/25) Learning By Design

    Readings:

    • Kolodner, J. L. (1997). Educational Implications of Analogy: A View From Case-Based Reasoning. American Psychologist, 52(1), 57-66. (Course Pack)
  • (11/27) Thanksgiving Holiday - No Class
  • (12/2) CoWebs

    Readings:

  • (12/4) Wrap-Up

    Due:


Late Policy

Each student may have a total of three late days over the course of the semester. Once you've used those up, late work will be penalized at a rate of one grade-step per day (max grade becomes A-, then B+, etc.) Work will not be accepted more than one week late. We always make an effort to return papers promptly; however, late papers may be returned substantially later.

Your presentations may not be late. Your take-home final exams may not be late.


Honor Code

This class abides by the Georgia Tech Honor Code.
Questions welcome--email the instructor or TA.

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