Virtual School Meanderings

June 9, 2017

Online Learning Consortium’s Call for Articles in the Online Learning Journal

Note this call for articles – which includes some focus on K-12 – that may be relevant to readers.

Good Morning,

The Online Learning Journal, formerly the Journal of Asynchronous Learning, wishes to invite the presenters at the 2017 AERA Annual meeting to publish in a special issue devoted to the Online Teaching and Learning Special Interest Group (OTL-SIG).  The Online Learning Journal (OLJ) is the Online Learning Consortium’s (OLC) scholarly journal providing readers with rigorous peer-reviewed research in a variety of educational contexts from k-12 to higher education in the US and internationally. The journal is currently in the midst of an extended effort to further develop quality and rigor in systematic inquiry in online learning in support of the larger mission of the Online Learning Consortium. OLC is the leading professional organization devoted to advancing quality online learning by providing professional development, instruction, best practice publications and guidance to educators, online learning professionals and organizations around the world.

About the Special Issue: Topics for the special issue include but are not limited to research on:

  • Strategies for student engagement
  • Virtual or online K-12 schools
  • Community of Inquiry, including Social Presence, Teaching Presence and Cognitive Presence
  • Online Interaction (e.g. Instructor, peer-to-peer)
  • MOOCs
  • Strategies for online discussions
  • Online group work
  • Blended learning and flipped classrooms
  • Integration of tools for online learning environments
  • Retention in online courses and programs
  • Instructor readiness
  • Designing for the online environment
  • Assessment strategies and issues

Qualitative, quantitative, and mixed methods research articles are welcome.

Submission Guidelines

If you would like to be considered for inclusion in the Special Issue, please complete the following form: https://goo.gl/forms/G7Pks01ckV4Nc71x2 .

  • Then, please submit manuscripts through the Open Journal System (OJS), the OLC journal system. Please select the Special Conference Issue: AERA Online Teaching and Learning SIG within the OJS submission process.
  • Author Guidelines include general APA Style 6th edition except for single-spacing requirement. Papers should be about 6,000-8,000 words. The Guide for Authors can be found here: http://onlinelearningconsortium.org/read/guide-authors/
  • For detailed assistance with APA style, refer to Purdue Online Writing Lab: https://owl.english.purdue.edu/owl/resource/560/01/
  • Please note that contributors will also be requested to serve as reviewers for this project.

Preliminary Timeline:

  • Intention to submit June 20th
    • send author and contact information, abstract from AERA presentation or updated abstract
  • Invited authors notified June 16-30th
  • Submission of full manuscript through the OLC journal system July 31st
  • Send out manuscripts for review on Aug 1st-4th
  • Return to editors on August 28th
  • Feedback from special issue editors on Sept 8th
  • Revised articles due back to editors by September 25th
  • Send manuscripts for copyediting on October 15 (absolute last day to be included)
  • Special Issue published December 15th (anticipated)

 

*Final acceptance notifications will not be delivered until after revised manuscripts have been submitted.

Special Issue Editors:

Dr. Jennifer C. Richardson (jennrich@purdue.edu)
Dr. Karen Swan (kswan4@uis.edu)
Marquetta Strait (straitm@purdue.edu)

Attachment: OLC Call for Articles from Online Teaching and Learning SIG_2017

January 17, 2017

Article Notice: “More Confident Going into College”: Lessons Learned from Multiple Stakeholders in a New Blended Learning Initiative

The third – and final – K-12 distance, online and blended learning article from yesterday’s [OLJ] New Online Learning Issue Published entry.

Aimee L. Whiteside, Amy Garrett Dikkers, Somer Lewis

 

Abstract

This article examined a blended learning initiative in a large suburban high school in the Midwestern region of the United States. It employed a single-case exploratory design approach to learn about the experience of administrators, teachers, students, and parents. Using Zimmerman’s Self-Regulated Learning (SRL) Theory as a guiding framework, this study explored surveys, face-to-face observation data, interview transcriptions, and focus group transcriptions to learn about different stakeholders’ experiences and their observations about student readiness for blended learning. As a result, the data suggested three major themes, namely how blended learning initiatives can promote autonomy and self-regulation, encourage inquiry and build relationships, and ultimately help students feel ready for college.

Keywords

Self-regulated learning, blended learning, K-12 education, case study research

Full Text:

PDF

References

Allen, I. E., & Seaman, J. (2015). Grade level: Tracking online education in the United States. Babson Park, MA: Babson Survey Research Group.

Babbie, E. (1973). Survey research methods. Belmont, CA: Wadsworth.

Barnard, L., Lan, W. Y., To, Y. M., Paton, V. O., & Lai, S. L. (2009). Measuring self-regulation in online and blended learning environments. The Internet and Higher Education, 12, 1-6.

Bertrand, W. E. (2010). Higher education and technology transfer: The effects of “techno-sclerosis” on development. Journal of International Affairs, 64(1), 101—119.

Clayton Christensen Institute for Disruptive Innovation. (2016). Blended learning. Retrieved from http://www.christenseninstitute.org/blended-learning/

Cicchetti, D. V. (1994). Guidelines, criteria, and rules of thumb for evaluating normed and standardized assessment instruments in psychology. Psychological Assessment 6(4),

—90.

Effeney, G., Carroll, A., & Bahr, N. (2013). Self-regulated learning and executive function: Exploring the relationships in a sample of adolescent males. Educational Psychology, 33(7), 773—796. doi:10.1080/01443410.2013.785054.

Garrison, R. & Kanuka, H. (2004). Blended learning: Uncovering it transformative potential in higher education. The Internet and Higher Education, 7(2), 95-105.

Garrett Dikkers, A., Whiteside, A. L., & Lewis, S. (forthcoming). Blending face-to-face and online instruction to disrupt learning, inspire reflection, and create space for innovation. In A. Whiteside,

A. Garrett Dikkers, & K. Swan (Eds.), Social presence in online learning: Multiple perspectives on practice and research. Sterling, VA: Stylus Publishing.

Garrett Dikkers, A., Whiteside, A. L., & Lewis, S. (2014, December). Do you blend? Huntley High School does. eLearn Magazine, 2014(12). doi:10.1145/2693839.2686759

Hattie, J. (2013). Calibration and confidence: Where to next? Learning and Instruction, 24,

-66.

Lee, T.H., Shen, P.D., Tsai, C.W. (2010). Enhance students’ computing skills via web-mediated self-regulated learning with feedback in blended environment. International Journal of Technology and Human Interaction 6(1), 15—32.

Moore, M. (1997). Theory of transactional distance. In D. Keegan (Ed.), Theoretical principles of distance education (pp. 22—38). New York: Routledge.

Nicol, D., & Macfarlane-Dick, D. (2006). Formative assessment and self-regulated learning: A model and seven principles of good feedback practice. Studies in Higher Education, 31(2), 199-218.

Orhan, F. (2007). Applying self-regulated learning strategies in a blended learning instruction. World Applied Sciences Journal, 2(4), 390—398.

Picciano, A.G. (2002). Beyond student perceptions: Issues of interaction, presence, and performance in an online course. Journal of Asynchronous Learning Networks, 6(1), 21-40.

Picciano, A. G. & Seaman, J. (2009). K-12 online learning: A 2008 follow-up of the survey of U.S. school district administrators. NY: The Sloan Consortium. Retrieved from http://www.sloanconsortium.org/publications/survey/k-12online2008.

Picciano, A.G. & Seaman, J. (2010). Class connections: High school reform and the role of online learning. Boston, MA: Babson College Survey Research Group.

Pintrich, P., & Garcia, T. (1994). Self-regulated learning in college students: Knowledge, strategies, and motivation. In P. R. Pintrich, D. Brown, and C. Weinstein (Eds.), Student motivation, cognition, and learning: Essays in honor of Wilbert J. McKeachie, Hillsdale, NJ: Lawrence Erlbaum Associates.

Pintrich, P., & Zusho, A. (2002). The development of academic self-regulation: The role of cognitive and motivational factors. In A. Wigfield & J. Eccles (Eds.), Development of achievement motivation. San Diego, CA: Academic Press.

Ryan, R., & Deci, E. (2000). Self-determination theory and the facilitation of intrinsic motivation, social development, and well being. American Psychologist, 55(1), 68-78.

Schunk, D. H., & Ertmer, P. A. (2000). Self-regulation and academic learning: self-efficacy enhancing interventions. In M. Boekaerts, P. R.

Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 631—649). San Diego: Academic Press.

Shea, P., & Bidjerano, T. (2010). Learning presence: Towards a theory of self-efficacy, self-regulation, and the development of a communities of inquiry in online and blended learning environments. Computers & Education, 55(1), 1721-1731.

U.S. Department of Education, Office of Vocational and Adult Education (2011). Just Write! Guide. Washington, D.C: U.S. Department of Education, Office of Vocational and Adult Education.

Weimer, M. (2009) What it means to be a self-regulated learner. The Teaching Professor.

Retrieved from http://www.facultyfocus.com/articles/teaching-and-learning/what-it-means-to-

be-a-self-regulated-learner/.

Yin, R. (2009). Case study research: Design and methods. 4th ed., London: Sage.

Zimmerman, B. (1990). Self-regulated learning and academic achievement: An overview.

Educational Psychologist, 25(1), 3-17.

Zimmerman, B. (2000). Self-efficacy: An essential motive to learn. Educational Psychology, 25, 82-91.

Zimmerman, B. (2002). Becoming a self-regulated learner: An overview. Theory into Practice, 41(2), 64-70.

Article Notice: Online Teacher Work to Support Self-Regulation of Learning in Students with Disabilities at a Fully Online State Virtual School

The second K-12 distance, online and blended learning article from yesterday’s [OLJ] New Online Learning Issue Published entry.

Mary Frances Rice, Richard Allen Carter, Jr.

 

Abstract

Students with disabilities represent a growing number of learners receiving education in K-12 fully online learning programs. They are, unfortunately, also a large segment of the online learning population who are not experiencing success in these environments. In response, scholars have recommended increasing instruction in self-regulation skills for these students, but whether teachers are able to promote self-regulation as part of their instruction and how they will do so remains unknown. The purpose of this qualitative study was to examine how practicing teachers provided self-regulation strategies to students with disabilities in a fully online learning environment. In this context, the teachers intended to offer self-regulation strategies to students, but they were largely unable to do so. This work has the potential to influence professional development programs for online teachers in the hopes that students with disabilities will be able to learn self-regulation strategies and ultimately be more successful.

Keywords

Self-regulation, practicing online teachers, students with disabilities, teacher thinking about strategies, K12 virtual schools, online learning policy

Full Text:

PDF

References

Barbour, M. K., & Mulcahy, D. (2004). The role of mediating teachers in Newfoundland’s new model of distance education.

Butler, D. L. & Winne, P.H. (1995). Feedback and self-regulated learning: A theoretical synthesis. Review of Educational Research, 65(3), 245-281.

Bernier, A., Carlson, S. M., & Whipple, N. (2010). From external regulation to selfâ€regulation: Early parenting precursors of young children’s executive functioning. Child development, 81(1), 326-339.

Boekaerts, M. & Corno, L. (2005) Self-regulation in the classroom: A perspective on assessment and intervention. Applied Psychology: An International Review, 54(2), 199-231.

Cavanaugh, C. (2007). Student achievement in elementary and high school. Handbook of distance education, 2, 157-168.

Clandinin, D. J., Murphy, M. S., Huber, J., & Orr, A. M. (2009). Negotiating narrative inquiries: Living in a tension-filled midst. The Journal of Educational Research, 103(2), 81-90.

de la Varre, C., Irvin, M. J., Jordan, A. W., Hannum, W. H., & Farmer, T. W. (2014). Reasons for student dropout in an online course in a rural K—12 setting. Distance Education, 35(3), 324-344.

Fernandez, H., Ferdig, R. E., Thompson, L. A., Schottke, K., & Black, E. W. (2016). Students with Special Health Care Needs in K-12 Virtual Schools. Journal of Educational Technology & Society, 19(1), 67-75.

Friedhoff, J. R. (2015). Michigan’s K—12 virtual learning effectiveness report 2013—2014.

Fritschmann, N. S., Deshler, D. D., & Schumaker, J. B. (2007). The effects of instruction in an inference strategy on the reading comprehension skills of adolescents with disabilities. Learning Disability Quarterly, 30(4), 245-262.

Gemin, B., Pape, L., Vashaw, L., & Watson, J. (2015). Keeping pace with K—12 digital learning: An annual review of policy and practice.

Graham, S., & Harris, K. R. (1993). Self-regulated strategy development: Helping students with learning problems develop as writers. The Elementary School Journal, 169-181.

Harris, K. R., Graham, S., & Mason, L. H. (2006). Improving the writing, knowledge, and motivation of struggling young writers: Effects of self-regulated strategy development with and without peer support. American educational research journal, 43(2), 295-340.

Marshall, C., & Rossman, G. B. (2014). Designing qualitative research. Thousand Oaks, CA: Sage publications.

Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational psychology review, 16(4), 385-407.

Sawyer, R. J., Graham, S., & Harris, K. R. (1992). Direct teaching, strategy instruction, and strategy instruction with explicit self-regulation: Effects on the composition skills and self-efficacy of students with learning disabilities. Journal of Educational Psychology, 84(3), 340-352.

Schunk, D. H., & Zimmerman, B. J. (2007). Influencing children’s self-efficacy and self-regulation of reading and writing through modeling. Reading & Writing Quarterly, 23(1), 7-25.

Schunk, D. H. (2005). Self-regulated learning: The educational legacy of Paul R. Pintrich. Educational Psychologist, 40(2), 85-94.

Watson, J., Pape, L., Murin, A., Gemin, B., & Vashaw, L. (2014). Keeping pace with K-12 digital learning: An annual review of policy and practice. Evergreen Education Group.

Watson, J., & Kalmon, S. (2005). Keeping pace with K—12 online learning: A review of state-level policy and practice. Naperville, IL: Learning Point Associates.

Wehmeyer, M. L., Smith, S. J., Palmer, S. B., & Davies, D. K. (2004). Technology use by students with intellectual disabilities: An overview. Journal of Special Education Technology, 19(4), 7-21.

Weinstein, C. E., Mayer, R. E., (1986). The teaching of learning strategies. In Wittrock, M. C. (Ed.) Handbook of research on teaching, 3rd ed. (pp. 315-327). New York, NY: Macmillan.

Zimmerman, B. J. (2008). Investigating self-regulation and motivation: Historical background, methodological developments, and future prospects. American Educational Research Journal, 45(1), 166-183.

Article Notice: Gender Differences in Online High School Courses

Today I wanted to highlight some of the K-12 distance, online and blended learning articles that were referenced in the [OLJ] New Online Learning Issue Published entry from yesterday.

Susan Lowes, Peiyi Lin, Brian R.C. Kinghorn

 

Abstract

Prior research has suggested that there may be differences in the ways that male and female students approach their online courses. Using data for 802 high school students enrolled in 14 online courses, this study explored gender differences in the interrelationships among online behaviors and course performance. The findings show that females were more active than males and that a higher degree of online activity and discussion forum viewing and posting was associated with better final grades, but the correlation was stronger for males than it was for females. Further exploration of posting behaviors revealed that females who received lower final grades were more active than males who received lower grades—they viewed more posts, wrote more posts, and wrote longer posts. These gender differences have implications for researchers, course providers, and course designers.

Keywords

online learning, LMS research, gender differences

Full Text:

PDF

References

Anderson, T. (2003). Getting the mix right again: An updated and theoretical rationale for interaction. The International Review of Research in Open and Distributed Learning, 4(2). http://www.irrodl.org/index.php/irrodl/article/view/149/230

Arbaugh, J. B. (2000). An exploratory study of the effects of gender on student learning and class participation in an Internet-based MBA course. Management Learning, 31(4), 503–519. http://dx.doi.org/ 10.1177/1350507600314006

Chapman, E. (2003). Alternative approaches to assessing student engagement rates. Practical Assessment, Research & Evaluation, 8(13). http://PAREonline.net/getvn.asp?v=8&n=13

Cho, M. H., & Kim, B. J. (2013). Students’ self-regulation for interaction with others in online learning environments. The Internet and Higher Education, 17, 69–75. http://dx.doi.org/10.1016/j.iheduc.2012.11.001

Davies, J., & Graff, M. (2005). Performance in e-learning: Online participation and student grades. British Journal of Educational Technology, 35(4), 657–663. http://dx.doi.org/10.1111/j.1467-8535.2005.00542.x

Dawson, S., McWilliam, E., & Tan, J. (2008). Teaching smarter: How mining ICT data can inform and improve learning and teaching practice. Hello! Where are you in the landscape of educational technology? Proceedings ASCILITE Melbourne 2008 (pp. 221–230). http://www.ascilite.org/conferences/melbourne08/procs/dawson.pdf

Hung, J.-L., & Zhang, K. (2008). Revealing online learning behaviors and activity patterns and making predictions with data mining techniques in online teaching. MERLOT Journal of Online Learning and Teaching, 4(4), 426–437. http://jolt.merlot.org/vol4no4/hung_1208.pdf

Hung, J., Hsu, Y., & Rice, K. (2012). Integrating data mining in program evaluation of K–12 online education. Educational Technology & Society, 15(3), 27–41. http://www.ifets.info/journals/15_3/3.pdf

iNACOL (International Association for K–12 Online Learning). (2013). Fast facts about online learning. Vienna, VA: International Association for Online Learning. http://www.inacol.org/resource/fast-facts-about-online-learning/

Johnson, R. D. (2011). Gender differences in e-learning: Communication, social presence, and learning outcomes. Journal of Organization and End User Computing, 23(1), 79–94. http://dx.doi.org/10.4018/joeuc.2011010105

Jonassen, D. H. (1999). Designing constructivist learning environments. In C. M. Reigeluth (Ed.), Instructional-design theories and models: A new paradigm of instructional theory (Vol. II, pp. 215–39). Mahwah, NJ: Lawrence Erlbaum Associates.

Liu, F., & Cavanaugh, C. (2011a). High enrollment course success factors in virtual school: Factors influencing student academic achievement. International Journal on E-Learning, 10(4), 393–418. https://www.learntechlib.org/p/33040/article_33040.pdf

Liu, F., & Cavanaugh, C. (2011b). Success in online high school Biology: Factors influencing student academic performance. Quarterly Review of Distance Education, 12(1), 37–54. https://rtsdettf.wikispaces.com/file/view/onlineHSBio.pdf

Liu, F., & Cavanaugh, C. (2012). Factors influencing student academic performance in online high school Algebra. Open Learning: The Journal of Open, Distance and e-Learning, 27(2), 149–167. http://www.tandfonline.com/doi/abs/10.1080/02680513.2012.678613

Lowes, S. (2014). A brief look at the methodologies used in researching online teaching and learning. In R. E. Ferdig & K. Kennedy (Eds.), Handbook of research on K–12 online and blended learning (pp. 83–104). Pittsburgh, PA: ETC Press.

Lowes, S., & Lin, P. (2015). Learning to learn online: Using locus of control to help students become successful online learners. Journal of Online Learning Research, 1(1), 17-48. https://www.learntechlib.org/d/149845

Lowes, S., Lin, P., & Kinghorn, B. (2015). Exploring the link between online behaviours and course performance in asynchronous online high school courses. Journal of Learning Analytics, 2(2), 169–194. http://dx.doi.org/10.18608/jla.2015.22.13

Macfadyen, L. P., & Dawson, S. (2010). Mining LMS data to develop an “early warning system” for educators: A proof of concept. Computers & Education, 54(2), 588–599. http://dx.doi.org/10.1016/j.compedu.2009.09.008

McSporran, M., & Young, S. (2001). Does gender matter in online learning? Research in Learning Technology, 9(2), 3–15.

Morris, L. V., Finnegan, C., & Wu, S-S. (2005). Tracking student behavior, persistence, and achievement in online courses. Internet and Higher Education, 8, 221–231.

Muthén, L. K. (2005, November 27). Negative Residual Variance [Msg 4]. Message posted to http://www.statmodel2.com/discussion/messages/11/555.html?1358188287.

Muthén, L. K., & Muthén, B. O. (1998-2015). Mplus User’s Guide. Seventh Edition. Los Angeles, CA: Muthén & Muthén.

https://www.statmodel.com/download/usersguide/Mplus%20user%20guide%20Ver_7_r3_web.pdf

Ramos, C., & Yudko, E. (2008). “Hits” (not “Discussion Posts”) predict student success in online courses: A double cross-validation study. Computers & Education, 50(4), 1174–1182. http://dx.doi.org/10.1016/j.compedu.2006.11.003

Rovai, A. P. (2001). Building classroom community at a distance: A case study. Educational Technology Research and Development, 49(4), 33–48. http://dx.doi.org/10.1007/BF02504946

Ryabov, I. (2012). The effect of time online on grades in online sociology courses. MERLOT Journal of Online Learning and Teaching, 8(1), 13–23. http://jolt.merlot.org/vol8no1/ryabov_0312.htm

Tsai, M.-J., Liang, J.-C., Hou, H.-T., & Tsai, C.-C. (2015). Males are not as active as females in online discussion: Gender differences in face-to-face and online discussion strategies. Australasian Journal of Educational Technology, 31(3), 263-277. http://ajet.org.au/index.php/AJET/article/view/1557/1278

Wang, A. Y., & Newlin, M. H. (2000). Characteristics of students who enroll and succeed in psychology web-based classes. Journal of Educational Psychology, 92(1), 137–143.

Watson, J., Pape, L., Gemin, B., & Vashaw, L. (2015). Keeping pace with K–12 digital learning. Durango, CO: Evergreen Educational Group. http://www.inacol.org/wp-content/uploads/2015/11/Keeping-Pace-2015-Report.pdf

Wei, H.-C., Peng, C., & Chou, C. (2015). Can more interactivity improve learning achievement in an online course? Effects of college students’ perception and actual use of a course-management system on their learning achievement. Computers & Education, 83, 10–21. http://dx.doi.org/10.1016/j.compedu.2014.12.013

Yukselturk, E., & Bulut, S. (2009). Gender differences in self-regulated online learning environments. Educational Technology & Society, 12(3), 12–22. http://www.ifets.info/journals/12_3/3.pdf

January 16, 2017

[OLJ] New Online Learning Issue Published

Please note several K-12 online and blended learning items from this announcement I received last week…

Dear Readers:

We recently published issue 20:4 of the journal Online Learning. We invite
you to review the new issue here:

https://olj.onlinelearningconsortium.org/index.php/olj

Thanks for your continuing interest in Online Learning and feel free to
share this announcement with colleagues and on social media.

best regards,

Peter Shea
Editor
Online Learning
University at Albany
State University of New York

Online Learning
Vol 20, No 4 (2016)
Table of Contents
https://olj.onlinelearningconsortium.org/index.php/olj/issue/view/51

Introduction
——–
Intro for special issue: AERA Online Teaching and Learning SIG
Jennifer C Richardson,  Karen Swan,     Marquetta Strait

Special Conference Issue: AERA Online Teaching and Learning SIG
——–
Students’ Perceptions of Learner-Learner Interactions that Weaken a Sense of
Community in an Online Learning Environment
Krystle Phirangee
Exploring the Effect of Scripted Roles on Cognitive Presence in Asynchronous
Online Discussions
Larisa Olesova, Margaret Slavin,        Jieun Lim
Culturally Responsive Teaching Knowledge and Practices of Online Faculty
Keri L. Heitner,        Miranda Jennings
Analysis of Discussion Board Interaction in an Online Peer-Mentoring Site
Regina Ruane,   Vera Lee
Gender Differences in Online High School Courses
Susan Lowes,    Peiyi Lin,      Brian R.C. Kinghorn
Online Teacher Work to Support Self-Regulation of Learning in Students with
Disabilities at a Fully Online State Virtual School
Mary Frances Rice,      Richard Allen Carter, Jr.
“More Confident Going into College” : Lessons Learned from Multiple
Stakeholders in a New Blended Learning Initiative
Aimee L. Whiteside,     Amy Garrett Dikkers,    Somer Lewis

Section II
——–
Introduction to Section II
Peter Shea
Relationships Between Minority Students Online Learning Experiences and
Academic Performance
Alex Kumi Yeboah,       Patriann Smith
Using Importance-Performance Analysis to Guide Instructional Design of
Experiential Learning Activities
Sheri Anderson, Yu-Chang Hsu,   Judy Kinney
Evaluation of Online Graduate Epidemiology Instruction and Student Outcomes
Jacqueline Knapke,      Erin Haynes,    Julie Breen,    Pierce Kuhnell, Laura
Smith,  Jareen Meinzen-Derr
Ethos and Practice of a Connected Learning Movement: Interpreting Virtually
Connecting Through Alignment with Theory and Survey Results
Maha Bali,      Autumm Lee Ann Caines,  Helen DeWaard,  Rebecca Hogue

________________________________________________________________________
Online Learning (OLJ)
http://olj.onlinelearningconsortium.org/index.php/olj

Next Page »

Blog at WordPress.com.