Telepresence and Engagement in Synchronous-Hybrid Learning Contexts

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Jul 202017
 

Telepresence and Engagement in Synchronous-Hybrid Learning Contexts

John Bell
William Cain
Cui Cheng
Amy Peterson
Ming Lei
Ying Hu
Ian Clemente
Jessica Sprick

 

Introduction

Here at the Synchronous Learning and Teaching Environments Research and Design (SLATE R&D) at the Design Studio, our work over the last few years has focused on Synchronous-Hybrid courses, with emphasis on telepresence and what students’ do in those environments. The purpose of this paper is to describe and present the Telepresence and Engagement Measurement Scale (TEMS), an instrument designed for implementation in synchronous-hybrid contexts. The TEMS instrument measures students’ sense of social presence, their embodiment, and their engagement in class and designed to be used for face-to-face and online students in higher education.

Background

Telepresence has been the focus of researchers in a number of different fields across the last decade and more. For example, researchers have examined how technology-mediated presence affects the interactions between healthcare providers and their patients (Broadbent, Stafford, & MacDonald, 2009; Robinson, MacDonald, & Broadbent, 2014; Salzmann-Erikson & Erikson, 2016), as well as interactions between coworkers in the workplace (Hinds, Roberts, & Jones, 2004; Mutlu & Forlizzi, 2008; Olson & Olson, 2000). Technology-mediated presence has also become the subject of educational research due to its potential to improve access to collaborative interactions and its unique impact on learning experiences (Garrison & Kanuka, 2004; Kristoffersson, Coradeschi, & Loutfi, 2013; Newhart, 2014; Power 2008)

At Michigan State University, SLATE R&D has developed and studied several models of synchronous-hybrid learning.. This work has included studies of balanced versus weighted designs in synchronous hybrid settings, i.e., distributing students equally or unequally (Cain & Henriksen, 2013); proto-robotic models, such as personal portals, where students go from being embodied together on a shared videoconference to having individualized screens on iPads (Sawaya, Bell, & Cain, 2013); linked classrooms where students and instructors from different campus worked together, as well synchronous small groups (Bell, Sawaya, & Cain, 2014; Cain & Henriksen, 2013).

Early research focused on issues precursory to the building a sense of being others and being in a place. Cain, et al. (2013) emphasized the importance of the senses and perception, specifically optimizing audio and video for learners. Subsequently, Sawaya and Cain (2014) found that the sense of being in a place and with others in a technology-mediated mode impacts social presence. This was followed up by research around videoconferencing and robotic telepresence technologies, such as the Double Robot and Kubi, which provided hybrid students a form of physical embodiment in the learning space (Bell, et al., 2016). This work was framed around the goal of reducing the gap that Sawaya and Cain (2014) found in hybrid students’ social presence, and that better social presence and increased autonomy in the hybrid students (Bell, Cain, Peterson, & Cheng, 2016).

Telepresence

The TEMS instrument is meant for use in blended learning environments that include a mix of synchronous and asynchronous components, and the use of technology-mediated presence, such as attending class via robot or video conferencing (Haans & IJsselsteijn, 2012). Our focus has been on telepresence, though it does have a sister construct, virtual presence. According to Haans and IJsselsteijn (2012), virtual presence refers to presence in a simulated environment, such as virtual reality, whereas telepresence refers to technology-mediated presence in an actual physical environment. Our instrument has been built around Haans and IJsselsteijn’s characterization of telepresence, so it may not be directly applicable to virtual environments.

In the conceptualization of telepresence presented by Haans and IJsselsteijn, the sense of being in a place has three major components: morphology, body schema, and body image. Morphology, when considered in respect to the human body, has to do with the charateristics or appearance of the body. Body schema pertains to the function of the body. And lastly, body image pertains to the reflexive awareness of one’s own body. These three dimensions of embodiment change in technology-mediated contexts, since one’s physical body is embodied through technological means, such a web-conference session on a computer screen. In the TEMS instrument, we used an adapted version of this model such that embodiment comprises projection, perception, and projection of perception. We define perception as the ability to see and hear, which corresponds with the concept of body schema. We define projection as the ability of others to see and hear the user, which corresponds with morphology. Lastly, we define perception of projection as the ability of a user to perceive how they are projecting into a space, which corresponds with body image.

In the TEMS instrument, we have extended concept of telepresence to include the sense of being with others, or social presence (Biocca, 1997; Biocca, Harms & Burgoon, 2003; Short et al., 1976). Following the work of Biocca et al. (2003), our definition of telepresence captures multiple dimensions: copresence, the awareness or sense of being with other people, psychological involvement, the sense of being with thinking, conscious beings, and behavioral engagement, the sense that one is interacting with others. Within psychological involvement, we included the concepts of intimacy, the sense of closeness to others (cued from eye-contact, emotional expression), and immediacy, the degree of psychological distance (cued from relationship type, degree of interest).

Engagement

Engagement has been defined in many ways, addressing both behaviors that take place within the classroom, such as coming to class prepared, asking questions, and activity outside of the classroom, such as civic engagement (Finn & Rock, 1997; Reschly & Christenson, 2012). In this work, the scope has been limited to engagement within the classroom and participatory patterns associated with behavioral, cognitive, and affective elements of engagement (Reschly & Christenson, 2012).

To create the engagement items for the TEMS instrument, we reviewed several existing instruments, such as the School Engagement Scale (Fredricks, Blumenfeld, Friedel, & Paris, 2005); Student Engagement Instrument (Appleton, et al., 2006); Student Engagement in Schools Questionnaire – Engagement Composite (Hart, Stewart, & Jimerson, 2011); Motivation and Engagement Scale (Martin, et al., 2014; Higher Education Authority, 2015); behavioral engagement items from Skinner, Kindermann, and Furrer (2009); a college student engagement measure by Handelsman, Briggs, and Towler (2005); and a student interest and engagement scale by Mazer (2012). Using these items as a starting point, we adapted items from these existing instruments that would capture behavioral engagement, i.e., what students do in class, cognitive engagement, i.e., what students think about in class, and affective engagement, i.e.,what students feel in class, in synchronous-hybrid classes.

Next Steps

The TEMS still needs to be validated. While our interviews with our study participants have provided evidence to suggest some face validity of the items, our next step is to conduct some validity tests of the items, such as cluster analysis, to ensure that the survey items load appropriately to their respective variables.

 Telepresence and Engagement Measurement Scale

Experience and Comfort
I am very skilled in participating in academic settings using robotic telepresence technology.
I am very comfortable in participating in academic settings using robotic telepresence technology.

Embodiment
I could easily see what I wanted to see.
I could easily hear what I wanted to hear.
I felt like people could see me when I wanted to be seen.
I felt like people could hear me when I wanted to be heard.
I had a good sense of how I appeared to others.
I had a good sense of how I appeared to others.

Social Presence
I felt like I was with those who were physically present in my class.
I felt like I was with those who were NOT physically present in my class.
I was aware of those who were physically present in my class.
I was aware of those who were NOT physically present in my class.
I felt close to those who were physically present in my class.
I felt close to those who were NOT physically present in my class.
I felt alone during the class.
I used VERBAL means (speaking and chat) to communicate with people who were physically present.
I used NON-VERBAL means (gestures, facial expressions, movement, etc.) to communicate with people who were physically present.
I used VERBAL means (speaking and chat) to communicate with people who were NOT physically present.
I used NON-VERBAL means (gestures, facial expressions, movement, etc.) to communicate with people who were NOT physically present.
I could tell when my efforts to communicate reached the intended people.
I could tell when my efforts to communicate had the intended effect.

Psychological Involvement
I felt like I was on the same page as others in the live sessions.
I felt that others in the live sessions acknowledged my point of view.
My opinions were clear to others in the live sessions.
I easily understood how others in the live sessions reacted to my comments.
I had a warm and comfortable relationship with others in the live sessions.
I felt that others in the live sessions cared about me.
I felt I was able to be personally close to others in the live sessions.
I was respected by others in the live sessions.
I was encouraged by others in the live sessions.
I was assisted by others in the live sessions.
I was treated equitably by others in the live sessions.
When I compare my experience to students in the other mode.. (If you were physically present, this question refers to people who were not physically present and vice versa.)
When I compare my experience to students in the other mode.. (If you were physically present, this question refers to people who were not physically present and vice versa.)

Engagement – Behavioral
I worked with students from this class to complete the course assignments.
I asked questions in class.
I participated during class discussions by sharing my thoughts and ideas.
I discussed course material with the instructor during class.
I listened attentively to my classmates’ contributions during class discussions.
I helped my classmates during class (e.g., answer questions).
I paid attention in class.

Engagement – Affective
The course material was relevant to my life (and/or career/research interest).
The course was interesting to me.
I had fun in class.
I liked the things we covered in class.

Engagement – Cognitive
I tried to connect new information with what I already know.
What I learned is important to my future.
I worked hard in class.
This course made me more knowledgeable.
The information in the course was useful.
I thought about what my classmates said in class even without talking.

References

Appleton, J. J., Christenson, S. L., Kim, D., & Reschly, A. L. (2006). Measuring cognitive and psychological engagement: Validation of the Student Engagement Instrument. Journal of School Psychology, 44(5), 427–445. https://doi.org/10.1016/j.jsp.2006.04.002

Bell, J., Sawaya, S., & Cain, W. (2014). Synchromodal classes: Designing for shared learning experiences between face-to-face and online students. International Journal of Designs for Learning, 5(1).

Bell, J., Cain, W., Peterson, A., & Cheng, C. (2016). From 2D to Kubi to Doubles: Designs for Student Telepresence in Synchronous Hybrid Classrooms. International Journal of Designs for Learning, 7(3).

Broadbent, E., Stafford, R., & MacDonald, B. (2009). Acceptance of Healthcare Robots for the Older Population: Review and Future Directions. International Journal of Social Robotics, 1(4), 319–330.

Cain, W., & Henriksen, D. (2013). Pedagogy and situational creativity in synchronous hybrid learning: Descriptions of three models. In Society for Information Technology & Teacher Education International Conference (Vol. 2013, pp. 291–297).

Finn, J. D., & Rock, D. A. (1997). Academic success among students at risk for school failure. Journal of Applied Psychology, 82(2), 221.

Fredricks, J. A., Blumenfeld, P., Friedel, J., & Paris, A. (2005). School engagement. In K. A. Moore & L. H. Lippman (Eds.), What do children need to flourish? (pp. 305–321). Springer. Retrieved from http://link.springer.com/content/pdf/10.1007/0-387-23823-9_19.pdf

Haans, A., & IJsselsteijn, W. (2012). Embodiment and telepresence: Toward a comprehensive theoretical framework. Interacting with Computers, 24, 211–218

Handelsman, M. M., Briggs, W. L., & Towler, A. (2005). A measure of college student engagement. The Journal of Educational Research, 98(3), 184–191.

Hart, S. R., Stewart, K., & Jimerson, S. R. (2011). The student engagement in schools questionnaire (SESQ) and the teacher engagement report form-new (TERF-N): Examining the preliminary evidence. Contemporary School Psychology: Formerly“ The California School Psychologist,” 15(1), 67–79.

Higher Education Authority. (2015). The Irish Survey of Student Engagement (ISSE): Results from 2015.

Hinds, P. J., Roberts, T. L., & Jones, H. (2004). Whose Job Is It Anyway? A Study of Human-Robot Interaction in a Collaborative Task, 19(1–2), 151–181.

Martin, A. J., Papworth, B., Ginns, P., & Liem, G. A. D. (2014). Boarding school, academic motivation and engagement, and psychological well-being: A large-scale investigation. American Educational Research Journal, 51(5), 1007–1049. https://doi.org/10.3102/0002831214532164

Mazer, J. P. (2012). Development and validation of the student interest and engagement scales. Communication Methods and Measures, 6(2), 99–125.

Mutlu, B., & Forlizzi, J. (2008). Robots in organizations: the role of workflow, social, and environmental factors in human-robot interaction. In Human-Robot Interaction (HRI), 2008 3rd ACM/IEEE International Conference on (pp. 287–294). IEEE.

Reschly, A. L., & Christenson, S. L. (2012). Jingle, Jangle, and Conceptual Haziness: Evolution and Future Directions of the Engagement Construct. In S. L. Christenson, A. L. Reschly, & C. Wylie (Eds.), Handbook of Research on Student Engagement (pp. 3–19). Boston, MA: Springer US. https://doi.org/10.1007/978-1-4614-2018-7_1

Robinson, H., MacDonald, B., & Broadbent, E. (2014). The Role of Healthcare Robots for Older People at Home: A Review. International Journal of Social Robotics, 6(4), 575–591.

Roseth, C. J., Saltarelli, A. J., & Glass, C. R. (2011). Effects of face-to-face and computer-mediated constructive controversy on social interdependence, motivation, and achievement. Journal of Educational Psychology, 103(4), 804–820.

Salzmann-Erikson, M., & Eriksson, H. (2016). Tech-resistance: the complexity of implementing nursing robots in healthcare workplaces. Contemporary Nurse, 52(5), 567–568.

Sawaya, S., Bell, J., & Cain, W. (2013). Introducing the Enhanced Personal Portal Model in a Synchromodal Learning Environment. In Proceedings of World Conference on Educational Multimedia, Hypermedia and Telecommunications 2013 (pp. 1349–1355). Victoria, British Columbia: Association for the Advancement of Computing in Education (AACE).

Sawaya, S., & Cain, W. (2014). Virtual Presence in a Synchromodal Learning Environment. In Proceedings of Society for Information Technology & Teacher Education International Conference 2014. Jacksonville, FL: Association for the Advancement of Computing in Education (AACE).

Short, J., Williams, E., & Christie, B. (1976). The social psychology of telecommunications. London ; New York: Wiley.

Skinner, E. A., Kindermann, T. A., & Furrer, C. J. (2009). A Motivational Perspective on Engagement and Disaffection: Conceptualization and Assessment of Children’s Behavioral and Emotional Participation in Academic Activities in the Classroom. Educational and Psychological Measurement, 69(3), 493–525.

Giving Feedback? Show It on the Big Screen

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Apr 242017
 
Virtual Flex Classroom helps make student “works-in-progress” public

Dr. Matthew Wawrzynski and his students in EAD 889 have been using in-class screen sharing to create a whole new way to make public, and to share feedback on, student group work that is still in progress.

Matthew Wawrzynski is an Assistant Professor in HALE (Higher Adult and Lifelong Education) and focuses on transitional experiences of college students, student access to higher education, retention, and student learning. Matt also teaches EAD 889, a Masters-level overview statistics course that reviews different quantitative research and assessment techniques.

For his course, Matt takes advantage of the affordances of the Virtual Flex Classroom in Rm. 132, Erickson Hall by utilizing in-class screen sharing to provide immediate feedback and modeling for students, and thus to increase the learning for his students. A typical class session goes like this.

Dr. Wawrzynski will give an interactive lecture, with student participation, to teach a particular statistical concept. After the lecture, students split up into groups in the classroom and go to student stations with computers around the room to employ the statistical methods that were just discussed. At that point, the work and discussions in each group normally would only be accessible to the members in a particular group.

But Matt has devised a way to let groups easily make public their work for the rest of the class, sometimes even as the work is taking place. The Virtual Flex classroom features four large monitors that all the students can see. Using the room’s custom Room Control software, Matt can project the screens of individual student station computers onto the large monitors around the room. The students are usually showing work they have done on SPSS, a statistics package that often requires complex decision making and knowledge of its different features.

As Matt puts it, “The beauty of the classroom is that it allows students to engage, then they have conversations about some of decisions they are making about the analysis… we can show it up on the screen and say, okay, let’s talk through how you made some of the decisions you made.”

Matt’s use of the Virtual Flex Classroom technology for in-class activity design is in keeping with current thinking about feedback, collaboration, and student learning. Research has shown that, in general, the more immediate the feedback, the better it is for student learning (Epstein, Lazarus, Calvano, & Matthews, 2002). Courses that deal with complex decision making, such as what analyses to run in SPSS and how to run them, can benefit from this immediate feedback from peers and professors. Traditional statistics classes often have students listen to a lecture then do their homework on their own, only to get feedback on their homework from their professor days or weeks later, and that feedback is generally invisible to each other. Matt uses Flex Classroom technology to significantly reduce the time for feedback and to make that feedback public as a model for others. In his words, “It allows students to see it, hear about it, read about it, do it, and get feedback while doing it”.

Epstein, M. L., Lazarus, A. D., Calvano, T. B., & Matthews, K. A. (2002). Immediate feedback assessment technique promotes learning and corrects inaccurate first responses. The Psychological Record, 52(2), 187.

College of Education Annual Technology Conference – 11/15/14

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Oct 312014
 

All faculty are invited to attend the College of Education annual technology conference on Saturday, November 15th from 8:30 am – 3:00 pm. Attend all or part of the conference to learn how instructional technology is being used in K-12 classrooms. Teachers, ISD and district technology integrationists, and faculty from peer institutions in lower Michigan are the primary presenters, sharing their experience and success with integrating technology into the classroom in a meaningful and pedagogically sound way. 

Through a continued collaboration between the College of Education, the MSU College of Education Alumni Association and the Master of Arts in Educational Technology Program, the conference will be FREE OF CHARGE to all attendees. Light breakfast items will be available before the keynote.

We are excited that Rebecca Garcia will be the opening keynote. Rebecca is the co-founder of CoderDojo NYC, a non-profit teaching youth to code. In 2013 she was awarded as the U.S. White House ‘Champion of Change’ for Tech Inclusion for her work to bring STEM education to underrepresented groups, especially youth and women. She was the youngest person to receive this award. Currently she is a Developer Evangelist at Squarespace, empowering people to build their ideas on the web. 

Follow this link to register: http://goo.gl/xanCyO 

Thank you for your time and we hope to see you on November 15th!