Online learning 4: How to teach online

1. Know your students: too busy to attend regular classes, struggling to combine job and family obligations with their studies. From andragogical perspectives, (1) for adult students to learn optimally they need to feel that what they study has relevance to their lives and/or their work; (2) that they know their own learning style and are given opportunities to work with the materials so it fits their way of learning

2. How to become an online professor?

• Create a professional website
• Effective communication - concise, responsive
  
• Right attitude - easy to work with, open-minded, flexible
• Well begun is half done
  
• Always backup your materials
  

3. Content

• content is less important than a well-structured classroom and peer interaction
• developed by content experts + instructional designers
• Online forum
• Keep a log of broken links, inconsistencies, and things to adjust and after thoughts/suggestions

4. Setting up the online classroom

• one section for each week/unit
• specific forum sections (for self intro, peer discussion, and current events and questions for the professor) shall be set up completely before the course starts
• discussion starters & intro messages for each forum section. (plus share info about yourself - encourage them to create a friendly meeting place)
  

5. Facilitation

• A shift from objectivist paradigm to constructivist paradigm
• A shift of power away form the professor to the students
• Clear expectations & timely feedback
• too many postings by the professor tends to hamper student interaction
• create a positive, open, and supportive learning environment
  

6. Feedback & grading

• Provide a list of assignments and deadlines (including examples, starting time, etc.)
• Organize your email and folders
• Feedback (a general part that discusses aspects of the assignment that pertain to most of the students and what the grading criteria are, and a student-specific part to discuss the strengths of the assignment and what can be improved)
• Check for plagarism (Google search)
• Self evaluation
• Late policy
• The main traits the students appreciate in a professor is friendliness, warmth, support, and clear expectations!

Online learning 3: Community, facilitation, and assessment

1. Emerging needs

• just-in-time knowledge has replaced the just-in-case, longer modules
• changing roles, expectations, responsibilities of mentors & learners
• more learner-centered, technology-enhanced communication (across time & space)
  

2. Interaction

• peers have a major influence on successful learning outcome, which is often not taken into account when designing training and academic courses (Palloff & Pratt, 1999)
• Key aspects of online interaction: a. community building, b. knowledge generation, & c. process management (Palloff & Pratt, 1999)
• a. Create spaces where students have the opportunity to interact about personal matters, build personal relationship and share issues not directly related to the course (reflection: web 2.0 tools such as Facebook and Twitter meet this need by providing profiles of the contact and extensive use of emotioncons to mitigate the challenge of the lack of non-verbal cue)
• b. Online interaction takes place without place and time restrictions, which is particularly conducive for knowledge generation in a constructive mode - meaning becomes shared through negotiation and interaction
• c. anytime learning (reflection: Now with Web 2.0 and wireless Web access, anytime anywhere/ubiquitous learning becomes increasingly feasible) - requires self-discipline, motivation (being part of an online community), online facilitator to set the initial rules & standards
  

3. Facilitation

• Community building - developing a conducive learning environment & encouraging shared construction of meaning (e.g., all each participant to create an online personality): a. clearly define the purpose of the group; b. create a distinctive gathering place for the group; c. promote effective leadership from within; d. define norms and a clear code of conduct; e. allow for a range of member roles; f. allow for and facilitate subgroups; g. allow members to resolve their own disputes
• Knowledge generation - adhere to andragogical rather than pedagogical principles: use facilitative mode to create a student-directed environment
• Process management - clear instructions (e.g., subdealines, online meeting times, number of posts required, presentation guidelines), virtual office hours, feedback
• Roles of the online facilitator: teacher, mentor, manager, and coach
  

4. Assessment

• A process of evaluating whether the online learning initiative has led to cost reduction, increased productivity, or a higher retention rate
• Formative evaluation: an ongoing process that takes place throughout the delivery of the course in order to fill gaps, and clarify and adjust content and delivery mechanisms
• Summative evaluation: evaluation that takes place after the course, most often in the form of grade. The frequency and quality of participation in the online interaction should be part of the grading basis.
• Pre- & post-test/survey (Reflection: for EDTEC120 we used Profile-IT survey) and various smaller modules (individualized)
  

References:

Palloff, R., & Pratt, K. (1999). Building learning communities in cyberspace. San Francisco: Jossey-Bass.

Online learning 2: Pedagogical theories & instructional design

Pedagogical frameworks

1. Andragogic Model

• let learners know why sth. is important to learn
• assist learners to direct themselves through info
• relate the topic to the learners' experiences
  

2. Objectivist Model (for short modules on specific concepts and skills)

• the world is completely and correctly structured
• intro-concept-example-practice-reflection (traditional textbook design)
  

3. Constructivist Model (for academically challenging longer modules and courses)

• knowledge is contextual, meanings are rooted in the indexed by experience
• problem-background-concept-analysis-solution (multidisciplinary, real-life problems)
  

4. Bloom's Taxonomy (Bloom, 1956)

• Knowledge: list, define, tell, describe, identify, show, label, collect, examine, tabulate, quote, name, who, when, where, etc.
• Comprehension: summarize, describe, interpret, contrast, predict, associate, distinguish, discuss, extend, etc.
• Application: apply, demonstrate, complete, show, solve, examine, relate, change, classify, discover, etc.
• Analysis: analyze, separate, order, explain, connect, classify, arrange, compare, select, explain, infer, etc.
• Synthesis: combine integrate, modify, rearrange, substitute, plan, create, design, invent, what if?, compose, formulate, prepare, generalize, rewrite, etc.
• Evaluation: assess, decide, rank, grade, test, measure, recommend, convince, select judge, explain, discriminate, support, conclude, compare, summarize, etc.
  

5. Problem-based learning (PBL)

• a professional preparation strategy that uses multifaceted, cross-disciplinary problems as the starting point for learning
• it draws on memory theory (activation of prior knowledge), problem solving theory (transfer concepts to new problems), and instance theory (pattern recognition)

Design and production of online content

1. Professional mode of production (e.g., for-profit online learning companies) - development team consists of SME (professor), advisory board, instructional designer - often takes 6 months

• (1) Planning (time varies): faculty preparation, draft of a working curriculum, time line, budget, work plan
  
• (2) Analysis and design (10 wks): curricular development, content analysis and initial design presentation
• (3) Development (10 wks): product development, faculty input, alpha lockdown (each module), beta lockdown (entire course)
• (4) Implementation (4 wks): implementation, evaluation, revisions and maintenance
  

2. Self-publication (web 2.0 is a catalyst?)

Online learning 1 - Adoption & implementation of innovations

Three challenges:

• 1. Professionals from diverse academic backgrounds have little shared knowledge which causes major problems when planning & implementing online ed.
• 2. Online instructors lack pedagogical background (e.g., constructivist approach, peer learning...)
• 3. Voice of the clients (students) rarely heard

Diffusion of innovations (Rogers, 1995)

• Why understand the innovation implementation process - 1. help understand why online learning initiatives succeed or fail; 2. how universities decide on policies that directly affect how instructors are required to deliver their courses
• Diffusion: the process by which an innovation is communicated through certain channels over time among the members of a social system (Rogers, 1995)
• Adopter (individual or organization) types: Innovators, Early Adopters, Early Majority, Late Majority, and Laggards.
• Three types of innovation decisions: 1. Optional (problem: member vs. system); 2. Collective (problem: time-consuming, costly) ; 3. Authority (problem: online learning companies take advantage) - reflection: can web 2.0 change the landscape?
• Disruptive technology (Christensen, 1997) - organizations are reluctant to venture into more risky but highly promising technologies (problem for web 2.0?)
• Adoption stages: 1. knowledge; 2. persuasion; 3. decision; 4. implementation; 5. confirmation
• Alternative of the change process (Fullan, 1991, p. 48): 1. initiation; 2. implementation; 3. continuation; 4. outcome

1. The initiation stage (intent): (1) selective perception; (2) attitudes forming (Contemplators, Adopters, & Rejectors); (3) adopter's sense of control; (4) teaching, administrative, and research aspects; (5) companies effect; (6) peer opinion & professional community; (7) administrative support

2. The implementation stage (overt change of behavior): (1) online learning represents a major shift of power (from instructors to instructional designers and learners, universities to corporate learning environments, f2f content to online, and now web 2.0 vs. commercial approach?); (2) non-research universities implement online learning faster (e.g., U. of Phoenix); (3) peer support & strong professional community; (4) business schools are always early adopters (because they stay close with the business front?)

3. The continuation stage (sustainability): (1) administrative support; (2) professional development; (3) facilitative educational methods

4. The outcome stage (assessment): (1) increased ability to apply what has been learned; (2) higher degree of satisfaction among educators and learners; (3) lower employee turnover; (4) the opportunity to cascade certain theories or methods down through the organization via online learning; (5) increased administrative efficiency

Reference:

Engvig, M. (2006). Online learning: All you need to know to facilitate and administer online courses. Cresskill, NJ: Hampton Press.

Christensen, C. M. (1997). The innovation dilemma. New York: Harper Business.

Fullan, M. G. (1991). The new meaning of educational change. New York: Teachers College Press.

3 Ways Web-Based Computing Will Change Colleges

By JEFFREY R. YOUNG

Cloud computing, one of the latest technology buzzwords, is so hard to explain that Google drove a bus from campus to campus to walk students through the company’s vision of it.

After students sat through a demo at computers set up nearby, they boarded the bus and got free T-shirts. The bus only stopped at colleges that had already agreed to hand over their student e-mail service to Google, which offers to run it for colleges free (Microsoft has a similar service and made a similar road trip).

At first I wondered why Google needed to demonstrate its popular e-mail service. Didn’t students already know how to click send? But when I hopped on the bus at George Washington University last month, I saw that the demos highlighted all the other Web services in its Google Apps for Education e-mail package for colleges, which includes a Web-based word processor called Google Docs, a Web-based spreadsheet program, and other tools.

Those tools are the cloud computing part—the term usually refers to programs that run over the Internet rather than locally on a user’s computer. And Google officials explained that many students don’t yet know about those new Web-based services.

Google’s bus is just one of many signs that cloud computing is starting to shake up campus technology. In the next five years, Web-based computing will likely bring important changes in how students study, how scholars do research, and how college information-technology departments operate.

Here are the promises and the challenges:

Sharing From Everywhere

At a summer program at the Massachusetts Institute of Technology that I sat in on last year, I asked students whether they had stayed up all night at the library finishing their final group projects, as the program’s organizers had predicted. One of the students looked at me as if I were crazy. Yes, he had worked late—until about 3 a.m.—but he had been at home by himself. The students all contributed to a shared document using Google Docs, which anyone in the group could edit online from anywhere. All of the students were essentially logged in to the same computer (in this case off at Google somewhere), one adding a paragraph at the end, another changing the font, and another rewriting the title. There was no longer any need to worry about getting everyone in the same room at the same time.

Such virtual collaboration is a key benefit of running something like a word processor on the Internet instead of on an isolated PC. Students can easily ask parents or faraway friends to edit their term papers remotely without having to send clunky attachments. Or students can set up a shared online document or spreadsheet to plan the next big fraternity bash. And that’s what is already happening at many institutions.

For professors, having documents stored in the Internet cloud means they can easily move from their home offices to their university office to the classroom without worrying about leaving the latest copy of their lecture notes behind. They can just log into Google Docs, or Microsoft’s Office Live or some other networked service, from any location. And the cloud-computing tools make it easier for professors to collaborate with colleagues on scholarly papers, too, supporting the trend of interdisciplinary research.

Supercharging Research

Google and other companies may be the innovators in cloud computing for things like word processing, but colleges have been leaders in using cloud computing for research.

Specifically, many colleges are setting up systems that let professors tap into supercomputers over the Internet using a standard PC. Then there’s a closely related trend of grid computing, which allows colleges to string together normal computers working in tandem over the Internet to provide the equivalent firepower of a supercomputer. The cobbled-together approach has meant that small colleges that could never afford a room-size supercomputer can set up something with the same processing bang on the cheap.

Basically, cloud computing is bringing supercomputing to the mainstream of research. “You reduce the barrier to use advanced computing facilities,” says Craig A. Stewart, associate dean for research technologies at Indiana University. (He will be co-moderating a panel about the promise of cloud computing at this week’s annual conference of Educause, the higher-education technology group.) And that ease of use means historians will increasingly join climate experts in using supercomputers to tackle their problems, he predicts.

Reshaping IT Departments

Cloud computing is also leading colleges to band together to offer services. After all, because servers that run Web-based software can be anywhere, why not get together with a few other colleges to build a joint data center?

That is already happening in Virginia, where a consortium of more than a dozen colleges is building the Virginia Virtual Computing Lab. The system will let students or professors at the different institutions use their own computers to access specialized software, such as 3-D modeling programs. The idea is to bring the kind of programs usually found in college computer labs right to students wherever they are, and one day it might make old-fashioned computer labs obsolete.

The Virginia project is modeled on a system already up and running at North Carolina State University, and that virtual lab is being shared with two community colleges and the University of North Carolina system.

“Students can’t really tell where it is since they’re going over the Internet,” says Henry E. Schaffer, coordinator of special IT projects and faculty collaboration at North Carolina State. “With a normal broadband connection, it just works.”

Meanwhile, colleges will outsource some services that it makes more sense for a big consumer company to handle, like e-mail, saving the colleges money to go build the services that they can do better.

The Challenges

That’s the rosy vision, but there are downsides.

The main one is privacy. Storing all your research notes on Google’s servers, for instance, may make the contents easier for government agencies or others to subpoena than if the data were on personal computers, because of the inconsistencies in current law, according to Daniel J. Solove, a law professor at George Washington University who explores the issue in his book, The Digital Person: Technology and Privacy in the Information Age. Companies like Google may be tempted to mine that data down the road and sell it to advertisers, especially if those companies fall on hard times, he said in a recent interview. “I think we need better laws for data security,” he said. “It is a problem that has not yet been solved.”

Also, there are human obstacles to collaborations like Virginia’s virtual computer lab, so just because such projects make good sense doesn’t mean that colleges will be able to pull them off if partners have conflicting ideas of how they should operate.

A new book by Educause that is scheduled to be released this week at the group’s annual conference captures the mix of promise and confusion that cloud computing poses today. Called, The Tower and the Cloud: Higher Education in the Age of Cloud Computing, it offers more than a dozen essays with predictions about the next stage of computing on campus. The book’s introduction argues that a cloud is an apt metaphor for the shift ahead: Clouds get harder to see your way through as you walk into them.

“We are letting go of a known and trusted toehold,” the book contends, “in favor of an uncertain one.”