I wanted to let you know about an exceptional opportunity.  A former professor of mine, Dr. Lloyd Rieber, will be offering a free online course (MOOC). Dr. Lloyd Rieber is a fantastic teacher, and he speaks in a language students can understand.  I cannot offer a higher recommendation for learning than with Dr. Rieber. As a graduate student, I had the pleasure to team teach with Dr. Rieber on multiple occasions, and Dr. Rieber participated on my dissertation research committee.  While I do not know exactly how this course will be organized, I can say that Dr. Rieber creates and delivers the highest quality instruction.

For you current students, this would be a great learning experience to both learn about Stats and live a MOOC.  Friends and colleagues, you may be able to recommend this opportunity to some of your students or friends.

Here’s the announcement and links:

From: Lloyd P Rieber <lrieber@uga.edu>
Subject: “Statistics in Education for Mere Mortals” a MOOC offered by Lloyd Rieber

I’ll be offering a MOOC on the topic of statistics in education. The MOOC runs from August 4-September 9, 2013 on Canvas.net https://www.canvas.net/ .

Well, the course will be open and online (and free), but we’ll have to see if the “massive” part happens.

Here’s a link to the course site:
https://www.canvas.net/courses/statistics-in-education-for-mere-mortals

I designed the course for “mere mortals,” meaning that I designed it for people who want to know about and use statistics as but one important tool in their work, but who are not — and don’t want to be — mathematicians or statisticians.

An important course requirement is that you have to be able to put up with my sense of humor (or lack thereof).

Here’s the formal course description:

This short course will provide a hands-on introduction to statistics used in educational research and evaluation. Participants will learn statistical concepts, principles, and procedures by building Excel spreadsheets from scratch in a guided learning approach using short video-based tutorials. Examples of specific skills to be learned include scales of measurement, measures of central tendency, measures of variability, and the computation of the following: mean, mode, and median, standard deviation, z (standard) scores, Pearson product-moment correlation coefficient (r), correlated-samples t test (i.e. dependent t test), independent-samples t test (i.e. independent t test), and a one-way analysis of variance (ANOVA).

The course is designed primarily for two audiences: 1) educational professionals who would like to be more informed about how to compute basic statistics and how to use them intelligently in their work; and 2) first-year doctoral students who want a short and friendly introduction (or brush up) to basic statistics before taking full graduate-level statistics courses. However, this course would be useful to anyone who wants a good, short, hands-on, friendly introduction to the most fundamental ideas of statistics in education.

Lloyd

**********************************************
* Lloyd P. Rieber
* Director, Innovation in Teaching & Technology for
*   the College of Education
* Professor, Department of Career & Information
*   Studies
* 203 River’s Crossing
* The University of Georgia
* Athens, Georgia  30602-7144  USA
* Phone: 706-542-3986
* FAX: 706-542-4054
* Email: lrieber@uga.edu
*…………………………………….
* http://lrieber.coe.uga.edu/
* http://www.NowhereRoad.com
*

internet and higher education journal cover

internet and higher education journal coverI just wanted to let you know that a former student of mine, Dr. Joanne Gikas, and I have a new article in press right now.  This is part of her dissertation research that focused on how teaching and learning occurred with mobile devices in higher education classrooms.  “Mobile Computing Devices in Higher Education: Student Perspectives on Learning with Cellphones, Smartphones & Social Media” is concerned with the student learning portion of the research, and the data were collected through focus groups with students at three different universities across the country.

We’re really pleased that this research is being published so quickly through The Internet and Higher Education journal.  It was submitted just a couple of months ago and is now in press and available through the journal’s Science Direct “in press” articles section.  That’s pretty amazing!  Here’s the abstract below and let me know if you are unable to access the article through your databases:

The purpose of this research was to explore teaching and learning when mobile computing devices, such as cellphones and smartphones, were implemented in higher education. This paper presents a portion of the findings on students’ perceptions of learning with mobile computing devices and the roles social media played. This qualitative research study focused on students from three universities across the US. The students’ teachers had been integrating mobile computing devices, such as cellphones and smartphones, into their courses for at least two semesters. Data were collected through student focus group interviews. Two specific themes emerged from the interview data: (a) advantages of mobile computing devices for student learning and (b) frustrations from learning with mobile computing devices. Mobile computing devices and the use of social media created opportunities for interaction, provided opportunities for collaboration, as well as allowed students to engage in content creation and communication using social media and Web 2.0 tools with the assistance of constant connectivity.

And if you have comments about the article or the questions about the data, please leave a comment. We’d love to hear what you have to say.

I have just received word from our librarians here on campus fantastic news.  ERIC has announced that they have restored full-text access to articles from 2005 to 2013.  This is great news!  Here is the announcement below.

ERIC Restores Online Access to Full Text from 2005-2013

ERIC has restored online access to more than 21,000 full-text PDFs with publication dates from 2005-2013.  These are documents and journal articles with permission to provide the full text that were previously restricted due to privacy concerns. Restrictions also have been lifted on the release of newly indexed, copyright-cleared full text with publication dates of 2005 or greater.

ERIC will continue to accept requests to restore access to older materials via the online form, and maintain the updated list of released documents. The Spotlight and alert areas on the ERIC home page at eric.ed.gov are kept up-to-date to keep you informed of the latest developments.

As you can see from the announcement above, you can request older documents from ERIC.  I had previously heard that ERIC had decided to prioritize their restoration based on those documents that were accessed or used or requested most often.  The online form to request older documents seems to be in this same direction.

A few years ago, I wrote a book chapter with Janette Hill at The University of Georgia on the complexities of implementing student-centered pedagogies, like project-based learning and problem-based learning.  This chapter “Weighing the Risks with the Rewards: Implementing Student-centered Pedagogy within High Stakes Testing” was published in Understanding Teacher Stress in an Age of Accountability edited by Richard Lambert and Christopher McCarthy, and it seems to be even more relevant as we head toward Common Core implementations and PARCC assessments in Tennessee.

In addition, I feel that there is a growing interest in inquiry and student-centered pedagogies within STEM disciplines. So, I thought I would provide the chapter and link in case you’re interested.

http://www.academia.edu/894278/Weighing_the_Risks_with_the_Rewards_Implementing_Student-centered_Pedagogy_within_High_Stakes_Testing

While somewhat theoretical, this chapter is grounded in the work I’ve done over the years in project-based learning and problem-based learning with K-12 and higher education.  In addition, it presents a balanced view of how students and teachers must adjust and work within their environments.

This Mess We're In
Creative Commons License Photo Credit: Toni Blay via Compfight

Over the past 5 or so years, a number of colleagues and myself have discussed the research around learning styles.  We have lamented the continuing attention that has been given to learning styles, particularly in teacher education.  This is of great interest to me. My dissertation research focused on the use of abilities and included a review of learning styles research.  As I wrote in my dissertation research:

Some of the strongest support for integrating learner differences into the classroom has the least research to endorse its use.  The intuitiveness of learner differences is a moving factor.  While we recognize individuals in a multicultural view—gender, ethnicity, and learning disabilities, for example—personalizing education to an individual seems as logical as any other accommodation that may be made.

Since my research a decade ago, though, there has been tremendous rigorous analysis of learning styles research. However, I continue to see blog posts by teachers, professional development specialists, and folks with huge followings on Twitter writing about learning styles.

In the past few days, my colleague Dr. Chuck Hodges at Georgia Southern University collated a number of the research resources we have discussed over the years into a Slideshare deck.  I encourage you to read it through and share it.  I’ve embedded it below, too. The slidedeck is pretty easily digestible.  It provides some of the strongest evidence we have about whether learning styles matter.

[slideshare id=18939517&doc=learningstyles-130416140105-phpapp02]

Intuition & Honesty

As a follow up, I completely “get” the intuitive desire and pull of learning styles.  It helps us to explain the uniqueness and individuality of learners — whether they are 8 years old or 40 years old.  As an instructional designer, I understand that it helps us believe we have taken in to account the variety of learners as spelled out by a learner analysis. And to be honest, I teach along side other teacher education faculty, and I know that learning styles as a topic is still being taught inside of our curricula. And again, if I’m being honest, I was an adamant believer in learning styles, previously, because I considered myself a “visual learner.” So, my thinking about this has had to evolve.

Believe me, I get it.

However, I implore you to consider the possibility that it may not matter.
For me, the baseline information is “learner preferences” are not determinants, or absolutes. So, developing content, or teaching in a specific manner, for a specific learner doesn’t make a difference.  Using multiple instructional strategies, multiple examples, multiple non-examples — yes, these will most likely matter.  However, using the same strategy for the same individual continually, just doesn’t matter.

If you’re so inclined, I would love to have your thoughts below.

Busy hands need no decoration
Creative Commons License Photo Credit: MD. Hasibul Haque Sakib via Compfight

I came across this blog post in my Zite feeds yesterday, and I thought that I should really share this for how timely it is to some of my students.  Right now, my doctoral class in academic writing is in the process of writing drafts of their literature reviews. So, I thought they might like a little support or scaffolding to help them write better (or stimulate their writing).

I know that students sometimes struggle with how to “say things” in their writing.  What I like about this post is that is organizes the different types of statements/arguments that you may make.  For example, here is a section under the “Argue” heading.

Argue

  1. Along similar lines, [X] argues that ___.
  2. There seems to be no compelling reason to argue that ___.
  3. As a rebuttal to this point, it might be (convincingly) argued that ___.
  4. There are [three] main arguments that can be advanced to support ___.
  5. The underlying argument in favor of / against [X] is that ___.
  6. [X]‘s argument in favor of / against [Y] runs as follows: ___.

via 70 useful sentences for academic writing.

Another Resource

Another resource that I use in my writing class is provided by UC Davis, and it has some excellent tips for academic writing, particularly with ways/methods to say things and verb tenses.

From Dr. Philip Pavlik, Institute for Intelligent Systems and Department of Psychology.  If you have a chance to go and hear about Betty’s Brain, I highly encourage it.  This is a fantastic example of technology-supported/enhanced learning in an open-ended learning environment.

Betty’s Brain: An open-ended learning environment that helps middle school students develop metacognitive strategies for learning science
Dr. Gautam Biswas, Vanderbilt University
Wed March 27, 2013 4:00pm – 5:20pm Cog Sci Seminar – FIT 405

Abstract
Over several years, our research team has developed Betty’s Brain, an open-ended multi-agent environment that utilizes the learning-by-teaching paradigm to help middle school students learn science. In Betty’s Brain, students teach a virtual Teachable Agent (TA) called Betty using a visual causal map representation. Once taught, Betty, can answer questions, explain her answers, and when requested by the student take quizzes, which are a set of questions created and graded by a mentor agent named Mr. Davis. The TA’s quiz performance helps students indirectly assess their own knowledge, and it also motivates them to learn more and improve their TA’s quiz scores. Overall, the learning and teaching task is complex, open-ended, and choice-rich. Thus, learners must employ a number of cognitive and metacognitive skills to achieve success. At the cognitive level, they need to identify, understand, and represent important information from online resources in the causal map format, and use the affordances of the system to assess Betty’s progress using quizzes. At the metacognitive level, they must decide when and how to acquire information, build and modify the causal map they are creating to teach Betty, check Betty’s progress, reflect on their own understanding of both the science knowledge and the evolving causal map structure, and seek help when necessary. Their cognitive and metacognitive activities are scaffolded through dialogue and feedback provided by Betty and Mr. Davis. This feedback aims to help students progress in their learning, teaching, and monitoring tasks.

Experimental studies run in middle school classrooms show that students learn science content and do develop some metacognitive learning strategies as they interact with Betty and Mr. Davis. However, a number of students fail to complete their teaching task because they lack an understanding of a number of the cognitive and metacognitive skills needed to become successful learners. We discuss recent additions to the Betty’s Brain system, primarily a model-driven assessments methodology for characterizing and evaluating the students’ actions as they learn in the environment. Our goal is to make the scaffolding provided by the system more relevant to the student’s current learning activities. This translates to a context-relevant, mixed-initiative conversational format for adaptive scaffolding, and we demonstrate that this helps students develop the cognitive and metacognitive skills they need to achieve success in their learning task.

Short Bio
Gautam Biswas is a Professor of Computer Science, Computer Engineering, and Engineering Management in the EECS Department and a Senior Research Scientist at the Institute for Software Integrated Systems (ISIS) at Vanderbilt University. He has an undergraduate degree in Electrical Engineering from the Indian Institute of Technology (IIT) in Mumbai, India, and M.S. and Ph.D. degrees in Computer Science from Michigan State University in E. Lansing, MI.

Prof. Biswas conducts research in Intelligent Systems with interests in hybrid systems modeling, simulation, and analysis, and their applications in two primary directions: (1) diagnosis, prognosis, and fault-adaptive control; and (2) their applications to develop STEM learning environments in K-12 classrooms. The most notable project with educational applications is the Teachable Agents project, where students learn science by building causal models of natural processes. He has also developed innovative educational data mining techniques for studying students’ learning behaviors and linking them to metacognitive strategies. He is currently working on projects that combine computational thinking with visual programming to help K-12 students develop a deep understanding of STEM content using model-building and simulation, and then applying these models to address real-world problems. His research projects in embedded systems and learning environments has been supported by funding from NASA, NSF, DARPA, and the US Department of Education. In one of the projects, working on Data Mining techniques to enhance aircraft diagnostic models in conjunction with Honeywell International researchers (NASA NRA) he won the 2011 Aeronautics Research Mission Directorate Technology and Innovation Group Award for Vehicle Level Reasoning System. He has published extensively, and has over 300 refereed publications.

Dr. Biswas is an associate editor of the IEEE Transactions on Systems, Man, and Cybernetics, Prognostics and Health Management, Educational Technology and Society journal, International Journal of Educational Data Mining and the Journal of Metacognition and Learning. He is currently serving on the Executive committee of the Asia Pacific Society for Computers in Education, a member of Executive Board of the Artificial Intelligence in Education Society, and is the IEEE Computer Society representative to the Transactions on Learning Technologies steering committee. He is also serving as the Secretary/Treasurer for ACM Sigart.