Distance Education Clearinghouse, University of Wisconsin- Extension:
List of Certificate Programs
http://www.uwex.edu/disted/certificates.cfm
Includes University of Wisconsin Madison, University of Wisconsin Stout, University of West Georgia, Appalachian State, California State Hayward, University of Illinois Springfield, Indiana University, Learning Resources Network, Manakau Institute of Technology, Nova Southeastern University, Pace University, Penn State, Portland State, St. Lawrence College, Simon Fraser, Texas A&M, Touro University, University of British Columbia, University of Calgary, University of Colorado Denver, University of Maryland, University of Washington
- Sheryl Hansen, Director, Professional Development Programs, Ohio Learning Network

Stephen F. Austin State University, Texas:
http://www.oit.sfasu.edu/facdev/certprogs.html
Online Instructor Certification Series: This set of three workshop series is designed for faculty who are developing or delivering complete web- based courses. After successfully completing the three series, faculty will be certified by the Office of Instructional Technology as an Online Instructor.
- Lauren Scharff, Ph.D., Director for the Scholarship of Teaching and Learning, United States Air Force Academy

New Mexico State University: http://extended.nmsu.edu/academics/otl/index.html
Graduate Certificate in On- line Teaching and Learning (OTL): for professionals in business, government, education, or other settings who want to develop their knowledge and skills in online teaching and learning. OTL utilizes technology- based environments to actively engage students in designing formal educational projects that meet professional objectives. The five 3- credit course sequence provides an intense immersion in a dynamic online environment and culminates in an online teaching practicum.
- Eugenia D. Conway, Associate Director, The Teaching Academy

University of West Florida:
Peer review for on- line courses: Quality Matters process, http://uwf.edu/atc/QM/
Training: Offered by UWF Academic Technology Center, Sloan- C, and Quality Matters.
Quality Matters (QM) is a faculty- centered, peer review process designed to certify the quality of online courses and online components. Sponsored by MarylandOnline, Inc. Quality Matters has generated widespread interest and received national recognition for its peer- based approach to quality assurance and continuous improvement in online education.
- Claudia J. Stanny, Ph.D., Director, Center for University Teaching, Learning, and Assessment; Associate Professor, Psychology

DePaul University: http://www.idd.depaul.edu/dots/index.html
DOTS: DePaul Online Teaching Series: DePaul Online Teaching Series
(DOTS) is a faculty development program that trains and assists faculty to become successful facilitators of online learning. The program builds online readiness among faculty through an immersive, hands- on experience. 36 Hours; includes hardware, software, support, stipend, and certificate.
- Todd Diemer, Teaching Commons Program Manager

Illinois Online Network (ION):
http://www.ion.uillinois.edu/courses/students/mot.asp
Master Online Teacher (MOT) certificate: part of the Making the Virtual Classroom a Reality series. The MOT is a non- credit award earned after successfully completing 6 courses in the MVCR series; there are three required courses, a core option, an elective, and a capstone practicum course. Over 400 people from around the world have earned their MOTs since the first recipients in 2001.
- Scott B. Johnson, Program Coordinator, Illinois Online Network

Ball State University:
Certification for Online Instruction (COI):
This certification is not required to teach online, but a few departments are leaning that way, and the associate provost is encouraging more departments to consider it.
COI is 6- week course based in Blackboard that includes modules on the following topics: Introduction to online teaching (theory/pedagogy); Content delivery; Communications; Assessment of student learning; Local resources Each of those modules is built around the same structure: Reflections on the teacher’s current face- to- face teaching practices in that area; Readings or videos; Asynchronous discussion board activity (with standard post/reply/summarize cycle); Individual assignment (Planning Document).
We think the strongest part of the class is this Planning Document.
After each module, participants are prompted to apply their learning and reflection to their planned online course. They actually plan out what they will do in the course (e.g., how they will deliver content- readings, lecture videos, interviews, virtual field trips, student- generated content, etc.), and what they need to do/learn to make that happen. By the end of the course, each participant has a concrete plan for their online course- very applied.
We have only been doing this for about a year and a half now (and are off this fall as we revise the course to match our Blackboard 9 upgrade), but we have gotten very good responses from everyone who finishes the class (obviously, a few drop out each semester when they realize the time commitment). The only down side to the program is that it takes a big time commitment for us to teach, and administrators didn’t factor that into our load when they asked me to create/teach the course.
- Greg Siering, Ph.D., Faculty Development Coordinator, Office of Teaching and Learning Advancement

The UVU Blackboard server now allows designers to require Respondus Lockdown Browser (LDB) on assessments. This means that if an assessment is set to use LDB, the end-user (test-taker) computer must have the free LDB software installed (Bb should prompt the user to install it before the assessment can be accessed). UVU’s Testing Center has installed LDB on all its computers and is testing it before next semester. We presume this is pointless unless the Bb assessment has LDB selected, but are looking into it. In any case where LDB is used to take an assessment, “lock down” happens according to Respondus’s descriptions–even if the exam itself is not triggered to require Lockdown. I asked Respondus to clarify the “switch” in Bb, and they responded this afternoon:

The “switch” in Blackboard and other course management systems helps insure (sic) that the assessment can only be taken with the Respondus LockDown Browser. Without enabling the switch, students can take the assessment using any browser they want, including the secure browser.

For Distance Ed this means that if an instructor wishes to use LDB, we must ensure proctor locations have the LDB software installed. This may require adding wording to the proctoring info web page. For the UVU Testing Center, if they make LDB the only web browser installed on lab computers, all assessments have no option but to be “locked down”.

Brian Swaney has written a lengthy post on LDB, explaining why he thinks it’s an awful idea that only inhibits cheating in limited scenarios, and though Brian’s post gets a little bit out of hand, I do agree with most of his points. Here’s a summary of these, some of which John Krutsch, Marc Hugentobler, and I have brought up in our conference sessions, “How to Cheat Online” and “The Cheatability Factor“:

1. LDB may encourage institutions to take advantage of broadly accessible but ill-suited environments for testing, like open student computer labs.
2. Unless the physical environment is also “locked down” the LDB will do little to inhibit cheating (crib notes, use of a 2nd computer, mobile devices).
3. Unless student identities are verified, LDB does not prevent impersonation (note: LDB doesn’t claim to).
4. There is a line between securing assessments and respecting student privacy. I don’t think LDB crosses it by any means, but Brian raises some legitimate concerns about requiring software installation.
5. All technology, including LDB, can be hacked.
6. The kinds of assessment best protected by LDB may not be good at assessing important kinds of learning. But LDB may be alluring as a (false) panacea for measuring all kinds of learning.

As our semester crawled into the second week and I began to enter scores and feedback for the students’ first assignment–a blog post–I noticed a couple unusual features:

1. When a student submits an URL for an assignment, Instructure grabs a screenshot of the rendered URL in addition to providing a hyperlink. This ensures that students actually have completed what they claim to have completed at the time of submission.
2. Students and instructors can each reply to an assignment’s score and feedback seamlessly within the system. For instance, after I submitted scores for this first assignment, one student explained in the assignment feedback why I failed to notice that she had in fact completed the assignment. I confirmed this, changed her score, and replied back, much like I would in private e-mail, but without any of the hassle of opening a message, choosing an addressee, etc.

Not only is this feedback discussion feature both seamless and the default, I can also use a built-in rubric, attach individual files (though Instructure has an even better way to upload assignment feedback en masse) and even record audio feedback inline (uses a Flash-based plug-in [still buggy for me on Win 7 in FF3]).

This is a great way to negotiate feedback and scoring with students. This also provides an opportunity for learners to engage in the assessment process. And since the features on this particular tool are easy and even intuitive to use, there is no excuse for accurate, timely corrective feedback that is understood by both instructor and learner.

Assumptions about online class size are often based on “traditional”, face-to-face (f2f) class experiences. Past studies suggest that the effectiveness of f2f classes is negatively tied to the number of students in the class, and that a range of 12-25 students may be an acceptable plateau for many classes. The ideal may in fact be a 1-to-1, mentor-like relationship between student and instructor–such as described by Bloom as the 2-sigma problem. We can also comfortably state that more students can equal more work for the instructor (more questions, more grading, more interaction)–potentially at the cost of instruction. At the very least we can assume that there are some class sizes at which learning will inevitably suffer (Drago & Peltier, 37), for all courses require some degree of student-instructor interaction, don’t they?

We therefore may be inclined to believe that there must be some correlation in online courses as there is in face-to-face courses. Indeed, a number of commentators on the issue recommend the same class sizes for online courses as have been recommended for traditional courses, even though there is still little research on the effect of class size in online courses. Toth & Montagna conclude that in ten years of research on the subject there is no consistent evidence of a predictable connection between student achievement and online class size. Why might that be? It may be that best practices in education are changing (informed by evolving learning theories and “21st Century” learner needs) such that student-instructor interaction is no longer critical. I think more likely that f2f and online courses are very different animals (though they are not always treated as such by instructors or students). Online courses have a number of specific dimensions of design and instruction that relate to their effectiveness. It may be that through careful course design and effective teaching strategies, online courses can reflect increased class size differently than face to face class size, reducing or even eliminating negative effects depending on the course.

Determining Optimal Class Size for Online Courses

Class size is not the sole predictor of teaching effectiveness in online environments; in “The Effects of Class Size on Effectiveness of Online Courses” Drago & Peltier cite five factors of teaching effectiveness: course structure, course content, instructor support and mentoring, instructor-student interaction, student-student interaction. Of these five they recognize only one as significantly and negatively impacted by class size: instructor-student interaction (31).

Though only one of five factors, instructor-student interacton is by no means a negligible dimension in online courses. Indeed, it may be more important to course effectiveness due to online learning’s larger transactional distance. The fact that students and teachers are rarely if ever in the same place at the same time may lead both to students and instructors to feel isolated, thereby reducing motivation. For students, transactional distance may have the added threat of making students feel unnoticed or unseen, a sense that may increase inclinations toward academic dishonesty. Transactional distance can be counteracted by increasing “presence” of instructor and students in the online environment.

The importance of presence and instructor-student interaction may vary from course to course. Every course is different, and courses and departments have different goals and outcomes to consider. Once we recognize this, we find questions that can help us determine optimal class size:

• Mentoring and feedback. Is learner success reliant on instructor-student interactions? Some courses thrive on learner interaction with informed and knowledgeable experts. If so, decreasing class size may increase instructor-student interaction.
• Teacher load. Do assessments require direct instructor review and feedback? Multiple-choice questions do not, but essay questions do. A course that can be accurately assessed with well-design multiple-choice questions may allow for a greater scale of students than one that needs one that requires more subjective review of individual assessments.
• Classroom community. Could an interdependent learner community support course objectives? If so, large class size may not be an obstacle, but a boon.
• Course curriculum. Are so-called “lower order” thinking skills (remembering, understanding) the focus of the course? This may allow for more objective assessments that can be automated, reducing instructor load.
• Course design. Is the course designed to provide rich, engaging content, relevant learning activities that help learners to take ownership of their learning? A well-designed course that encourages and supports learner independence is probably less reliant on class size for its effectiveness.
• Technology training. Is the instructor fluent with the technology? If s/he is capable of navigating the system rapidly and interacting with students using the best available tools, this may allow for more instructor-student interactions at less cost to their load.
• Course management. Has the instructor good online course management and time-saving strategies? Such strategies can reduce the load of online teaching, allowing instructors to facilitate more students.

Though these questions aim at the core issues of curriculum, course design, and teaching of online courses, they unfortunately are too subjective to predict real numbers for online class size. One must therefore base actual enrollment caps on experience, and it is here that we might as well look to f2f class size as a starting point. It is probably less harmful to students if class size starts as small as possible, increasing semester by semester as informed by both the student and the instructor experiences.

In doing so, here are some ideas to support student success in large online classes without overly taxing the instructor:

• Understand realistically how the online course impacts your faculty load.
• Do not write-off the students as “on their own” or think of Instead, build-in extensive support and maximize contact with students using discussion forums and mass e-mails.
• Invest in developing or implementing cohesive, dynamic, and engaging online course materials as a means of improving the online course overall.
• Train instructors to use the technology to their best benefit, thereby decreasing fear and frustration with the technology while reducing wasted time.
• Teach instructors course management strategies (Turoff & Hiltz) aimed at large courses.
• Shift responsibility for non-critical tasks (i.e. answering e-mail) from the instructor to graders or teaching assistants if possible.
• Leverage class size to the benefit of the students by growing communities of learners, e.g. through groups, peer assessments, etc.

I’m sure there are more ideas out there, and from folks with more experience with large class sizes than me. The real point of this posting is to foster the dialogue through which we might come to practical solutions.

References

• “Class Size – A Dangerous Discussion?” The TLT Group. Retrieved from http://www.tltgroup.org/ProFacDev/DangerousDiscussions/ClassSizeHome.htm
• Colwell, Joy. (2004). “The Upper Limit: The Issues for Faculty in Setting Class Size in Online Courses”. In Proceedings of Teaching Online in Higher Education 2004. Retrieved from http://www.ipfw.edu/tohe/Nov10.htm
• Drago, W & Peltier, J. (2004). The effects of class size on effectiveness of online courses”. Management Research News, 27(10) pp 27 – 41. Retrieved from http://www.emeraldinsight.com/10.1108/01409170410784310
• Online class size: Balancing quality and cost. (2000). Distance Education Report, 4(17), 3.
• Toth, L.S. (2002). “Class size and achievement in higher education: A summary of current research”. College Student Journal, 36(2) pp. 253-261.

Instructional Design & Development

1. ADDIE, Dick & Cary, and other ID models useful to revisit and reflect upon, especially for planning of critical stages of course design. Models do not necessarily inhibit rapid prototyping. UVU IDS might rethink how its course design process fits into such models (instead of immediate prototyping do we first analyze needs, course objectives, then outline content in design? Prototyping should be mid to late design phase).
2. Build instructional design models into project mgmt software as template. We in UVU IDS do something like this with dotProject, but could more explicitly label phases to provide data documentation and data.
3. Log instructional patterns (e.g. activities, interactions, assessments) and create “templates”.
4. Brainstorming ideas: aim for quantity not quality (no negations), stock conference room with treats and toys, limit to 1 hr/break & flow, focus everyone on the task, use online shared docs.
5. In design phase, instead of lists of info, make visual representations like wireframes & site maps. Let it be basic, ugly.
6. Tame your use of media to reduce cognitive load (read Clark’s Efficiency in Design again).
7. Avoid novelty for novelty’s sake (bad example: wave runner game with multiple choice questions, our Frogger game).
8. Try rapid e-learning dev tools like Captivate, Articulate, and Rapid Intake, but beware of outputs that aren’t accessible, web standards format.
9. More often than not Flash is just flashy.
10. PowerPoint continues to be abused by presenters from around the world, resulting in mind-numbing, soul-sucking internments. Folks talk about PPT design in terms of how many bullets, words, fonts per slide, with nearly no mention of “Presentation Zen”.
11. Also, a PPT designed for a (classroom) presentation is not elearning, even if you convert that PPT to Flash with Captivate. @BrianDusablon says #1 problem in e-learning is PPT. (#2 is systems that put obstacles between learner and learning.)
12. However, you can use PPT as an effective e-learning prototyping platform, if not a complete and robust authoring platform.
13. Surprise! Corporate training wants demonstrable outcomes, not rubrics that assert generalized ideals of quality based on theory. How well do our distance learning “quality” rubrics (QM, Chico) measure the actual effectiveness of learning experiences at helping students meet learning objectives? Isn’t that more important than, say, the 7 principles?
14. Though the session was canceled, it appears possible to use Google Spreadsheets as a data source for live e-learning content generation (think flashcards, quizzes)
15. UVU IDS should create all lesson discussions, assignments, and assessments as plain text files WITHIN the lessons folder, until Common Cartridge XML becomes useful on Moodle and Bb Vista.
16. URLs from augmented reality games session: http://argology.org, http://argn.com, http://unfiction.com

Questions

1. Does UVU IDS have enough accurate dotProject data yet to estimate the hour-cost of a new online course?
2. Non-linear ID is still popular, but is it effective? Have we passed the point at which hypertext inhibits learning and focus?
3. Where are communities that share DTDs and schemas, esp for e-learning? Does our XML DTD match any other known e-learning DTDs? (Really only Common Cartridge)

Reading List

1. Goal-based learning design a la Robert Schank
2. Humanizing education articles
3. Videogames and Education: Humanistic Approaches to an Emergent Art Form by Harry J. Brown
4. Chico State’s latest vers. of ROI
5. Survey of Instructional Development Models by Kent L. Gustafson, Robert Maribe Branch
6. Any empirical research on linear vs. non-linear (hypertextual) learning outcomes

Software Demo List

• Articulate (rapid e-learning development)
• Captivate (rapid e-learning development)
• ProForm / Unison (rapid e-learning development)
• Jing (screen capture)
• Agilix BrainHoney (LMS/learning system)

Of course, prior to the conference Ken and I will have to work pretty aggressively with Clark Nielsen and John Krutsch to ensure that the mod’s features and functionalities are stable and presentable.

1. The Cheatability Factor at Distance Teaching and Learning 2008, Madison, Wisconsin
2. How to Cheat Online & The Cheatability Factor at Teaching with Technology Idea Exchange 2008, Orem, Utah

Here are some details, reproduced from the proposals:

Promotional Summary

What is your online course’s “cheatability factor”? 75% of students have admitted to cheating during their college career, and according to some studies online assessment makes cheating easier. This session considers technical, philosophical, and environmental factors that may increase or decrease the cheatability of online courses from design to delivery, and presents a rubric used to assess those factors.

Objectives and Description

Presentation objectives:

Participants will..

1. Discover the extent to which cheating-related problems exist in online education and online-based assessments
2. Consider factors that may contribute technologically, philosophically, or environmentally to online cheating
3. Examine a rubric used to measure the “cheatability” of online course
4. Discuss practices and strategies to avoid or minimize the impact of cheating

Presentation description:

Nobody wants students cheating in their online class, yet an estimated 75% of students have admitted to cheating during their college career, and according to some studies online assessment makes cheating easier. The problem is not only one of practical importance for educators, it is one of growing importance to instructional technologists, administrators, and anyone else with a vested interest in the validity and reputation of distance education and technology-enhanced teaching.

This session will first present information and collected research data that summarizes the state of cheating in higher education in general, and in distance education specifically. While a general awareness of the pervasiveness of cheating may be in and of itself an eye-opener to many educators and administrators, the motivations behind cheating and the responsibility teachers have to recognize their own influence on cheating can provide an alternative perspective on what is normally considered a quite simple choice. McClusky’s theory of Power-Load-Margin, for instance, informs teachers of the impact they may have on students’ lives, and the impact students’ lives have on their studies, both of which can lead students to choose to cheat. A number of environmental factors are particularly salient in online courses, such as ambiguity of definitions of cheating, actual or perceptual “distance”, level of instructor-student interaction, individual relevance or meaningfulness of activities and assessments, etc. Additionally, there are a number of more technical and technological factors that can increase or decrease both a student’s propensity to cheat, and his/her ability to cheat.

By considering these technical, methodological, and environmental factors, Distance Education at Utah Valley University has developed a rubric to assess online courses and report on potential factors that may increase or decrease the cheatability of online courses from design to delivery. This rubric is (1) provided to teachers engaging in distance education course development or instruction, (2) made available to administrators and department chairs as an example of our mutual interest in preserving the integrity of online education, and (3) implemented internally as a tool in our course design process to better evaluate and recommend online assessments before, during, and after an online course is delivered.

Because cheating itself is a complex and sensitive issue informed by experience and diverse perspectives, this session seeks to engage participants in a dialogue on cheating, online assessments, and technology. We predict there will be naturally flowing discussion and debate between participants who may favor one approach over another, e.g. a “direct assault” approach which seeks to thwart any and all attempts at cheating using technology or applied strategies, vs. “hearts and minds” pedagogical approaches that focus on course environment, assessment design, and student engagement.