OLC Accelerate 2019 - Featured Sessions

This panel of seasoned individuals with experience in higher education and elearning, includes an adjunct faculty, a Chief Learning Officer, a full-time faculty member, a Director of Research, and a Director of Online Learning, with a moderator. The panel will present several challenges faced by adjuncts and institutions, the effective practices and models in training, supporting, and ensuring the success of online adjuncts in their work to teach students and represent the college or university, and a pathway forward for all educational practitioners working with adjunct faculty.

Panelists will share items from the literature and from industry standards in support of the pedagogy, andragogy, and effective models. Participants are encouraged to bring questions from their own professional or institutional examples.

By the Numbers – Increase in Part-Time Faculty

As of 2016, adjuncts, also known as part-time faculty or contingent faculty, make up just under 50% of the faculty at four-year and master’s level institutions of higher educations. At two-year colleges, over 65% of the faculty are teaching part-time (“AAUP”, 2018). This number does not include graduate assistants in a teaching role. Between 2008 and 2012 part-time faculty at post-secondary institutions increased 18% (“GAO”, 2017).

Responsibilities

In the 2017 U.S. Government Accountability Office report on the contingent workforce in higher education, administrators of colleges and universities interviewed shared that “part-time contingent faculty generally focus solely on teaching” (“GAO”, 2017, para. 2). However, responsibilities of the those hired to focus on teaching seem to increasingly widen in scope.

Overview Benefits and Challenges

As of 2012, more than half of the faculty teaching part-time make less than $35,000 a year, and that is with many of the instructors teaching at multiple institutions (The Coalition on the Academic Workforce, 2012). While there are benefits to part-time teaching, such as a flexible schedule and time to focus on the students, there are limitations which affect the adjunct faculty member professionally and personally. From the U.S. Government Accountability Office report of 2017, of those contingent faculty surveyed the following were listed as disadvantages to the role: uncertainty due to short-term contracts, untimely contract renewals, pay – including lack of compensation for some of their work, limited career advancement opportunities, no voice in institutional decision-making, and not having certain institutional support (“GAO”, 2017, para. 5).

The American Association of University Professors state that the current trends in faculty hiring provides an illustration of a “problem of instability that contingent faculty have throughout all academic institutions” (Flaherty, 2018, para. 16). Tenure, for full-time faculty, has been seen as insurance for a continued position at the college or university; however, for part-time faculty such an option is not available. Such instability may stem from insecure and unsupported positions, little job security, and inadequate due process protections (“AAUP, 2018; “GAO”, 2017; Flaherty, 2018).

Recruitment and Training

Inherently, educational institutions want quality instructors to teach their students. As such, and also to align with accreditation agencies, faculty must have subject-matter expertise and academic credentialing in their field of study. With the increase in elearning courses and training opportunities for students and professional learners, colleges and universities may seek part-time contracted faculty with prior online teaching experience. However, not all desired faculty, especially those currently in the industry offering real-world practitioner knowledge and skills, may have backgrounds in online teaching let alone online course design and/or use of a particular Learning Management System (LMS).

Hiring is one thing, retention of an employee is another. There is less cost, in monies and resources, to retaining quality employees. Quality contingent faculty may be hired, have a difficult onboarding experience and/or low enrollment which equates for their particular contract for low pay and determine that there is less hassle and more opportunities for pay at other institutions (Edmonds, 2015).

Conversely or concurrently, these part-time instructors may have experience in online education and teaching and be superb deliverers of content, however, if the institution does not support the educator in their onboarding and/or or training, they may not be able to best perform their expected role.

Design considerations are, at times, a concern for faculty as instructors are typically hired as subject matter experts in their field and not instructional designers. Some may balk at the need to learn a system which provides the medium for online learning or the tools and strategies used to design or even instruct such courses. Though there are opportunities for professional development and for leveraging the expertise of those in an institution, faculty may see the design process for blended and online learning time consuming, arduous, and complex (Freeman & Tremlay, 2013).

Institutional Support and Human Costs

The rise in part-time, or contingent faculty, may have correlation to a decrease in the budgets available for salaries and benefits for full-time faculty. As a way to cost cut, colleges and universities may hire multiple part-time faculty at a much lower pay rate, and without benefits, allowing for cost savings.

Support for adjuncts and collaboration with other parts of the institution open lines of communication which promote sharing of resources as well as problem solving for instructional issues in the classroom. Development of assets with librarians, instructional designers, and fellow faculty as well as from repositories of other shared content address the transfer of learning and application of strategies to increase engagement with students. Tools aid in the design and delivery of instruction (Beetham, 2013). Connections to concepts help students tune into the course. The cognitive load is lightened through well designed instructional assets (van Merrienboer & Ayers, 2006).

Conditions of Work

Colleges and universities may provide training and professional development and invites to meetings and opportunities to participate in committees, however, some adjunct faculty are hustling between full-time day jobs or multiple gigs of part-time teaching and/or other contracted or consulting roles. As such, a determination needs to be made by the institution – and the program or department – of what are the required items for adjunct attendance and participation and what would be nice.

Clear expectations are important. A college may impart to the adjunct that the course will be turn key and set up the faculty to do minimal design updates – course instructor information, syllabus upload – and then focus on prepping for instruction. Yet, upon receiving the course, there may be numerous corrections, technology issues, or other design items now put upon the faculty to fix prior to course start and often on their own. Additionally, institutions may offer adjuncts a blank shell and a previous semester syllabus and, for the same pay as teaching part-time in a face to face course, require the instructor to now design the course online.

Impacts on Students, Institution

Interestingly, some research has indicated students taking more courses from adjunct faculty may have a lower success, persistence, and matriculation rate than students taking more classes from full-time faculty (Edmonds, 2015). Variables influencing such outcomes are wide-ranging.

Depending on type of post-secondary institution, and faculty teaching models, some universities may relegate the larger survey courses or first year student courses, which may be general education classes, to the part-time faculty. Connecting back to the training and/or sharing of expectations by the institution with the adjunct, the faculty member may not be aware of policies or given the resources to support students best in their learning and success. Additionally, faculty may not have been given critical resources to prepare for the course in time or at all – for example the course textbook before class start.

As that online teaching is not yet accepted by all institutions and administrators as equal to, or even better in, the quality of face to face instruction, some faculty may be concerned about “commitment to scholarship” (Ubell, 2017, para. 3) and status. And the consideration of quality of online content and the ability to have valued instruction in such mediums is still a question amongst our fellow colleagues at various institutions (Ubell, 2017).

Faculty who have limited time on campus or online due to other obligations – commuting, day jobs, limited connections or technology – may also unintentionally impact student success. Making space, virtually or on site and with adequate supports and resources, for adjuncts may not only increase a sense of support and connection back to the institution but also offer further connections to students (Edmonds, 2015).

During this session, the panel of experts will share challenges faced by adjuncts and the institutions which employ them, effective models and practices to support and develop contingent faculty, and a way forward for all educational institutions to develop pathways for adjunct, student, and institutional success.

Federal State Authorization Regulations for distance education have been in erratic disarray for almost ten years. I have often called this crazy road to regulation the Federal Regulations Groundhog Day, in reference to the Bill Murray movie. It has been a long road, but we will see in this session if we finally have reached the end of the Groundhog Day loop.

We have seen stops and starts to the discussions, releases, and effective dates of federal regulations for state authorization. You may wonder why the Department wishes to regulate the activities of the institution that occur in other states. The main purpose is consumer protection. Federal State Authorization Regulations for distance education are intended to tie Title IV HEA participation by the institution to state oversight and institutional compliance with states. When the first release of a federal regulation occurred in 2010, it awakened the states to realize that activities of out-of-state institution were occurring in their states. Many states began to be more intentional in their enforcement of state regulations or they developed new regulations to provide oversight related to the surge of online courses that were being provided across state lines. The states wish to protect the students located in their states to ensure that the institutions follow their state’s requirements.

It is often lost on some institutional staff members, that States have the right to exercise control over the activities that occur within their State. Thanks to the Tenth Amendment of the U.S. Constitution, States generally control educational policy. Therefore, it has always been within the purview of the States to provide oversight of activities that occur in their State including online courses, field experiences, marketing, recruiting, etc. etc.

It is because of the understanding of the important role of the States for institutional oversight, that the State Authorization Reciprocity Agreements (SARA) were developed. Years prior to their ultimate creation, key stakeholders developed plans to meet the needs of students, institutions, and the states to provide oversight and flexibility to offer certain out-of-state activities in a consistent manner rather than by varied state processes. States voluntarily joined SARA to provide opportunities for their institutions in exchange for managing compliance in a consistent plan across member States. Most States required legislative action to join SARA.

Since the first release of final Federal regulations on this issue, that were ultimately vacated on procedural grounds, there has been almost ten years of confusion. The first regulations were vacated by the Federal courts due to procedural error by the Department, the Department attempted, in 2014, to proceed with negotiated rulemaking to develop new regulations. The rulemaking did not end in consensus. Therefore, the Department could write the rules. In the summer of 2016, in the last year of the Obama administration, the Department released proposed regulations that were full of ambiguities and misalignment with state regulation for which the Federal regulations were intended to support. Final regulations were not released until December 19, 2016 causing the effective date of the regulations to be July 1, 2018. The effective date was to be 18 months into a new Presidential administration. Many higher education institutions and organizations submitted comments and requests for information and guidance at every opportunity. The Department released the announcement of the delay of the 2016 Federal regulations on July 3, 2018 for the purposes of review and revision.

In August 2018, the Department announced its intention to enter into negotiated rulemaking to review and revise more than 20 different issues related to innovation, accreditation, state authorization, and distance education. Meanwhile in August, the National Education Association and California Teachers Association filed a lawsuit in the U.S. District Court in the Northern District of California regarding the illegal delay of the 2016 regulations.

Beginning in January, the Accreditation and Innovation negotiated rulemaking committee met through the winter months of 2019 along with the unprecedented addition of three subcommittees to provide research and advise the main committee. It was a surprise to all that on April 3, 2019 the main negotiated rulemaking committee came to consensus on all issue presented to the committee. State Authorization related regulations as well as professional licensure disclosures were review and revised in the consensus regulations. Based on the consensus language, the Department released proposed regulations for public comment on June 12, 2019.

To add to the drama, on April 26, 2019 the U.S. District court ruled for the plaintiff and directed that the delay of the 2016 regulations be vacated but stayed the ruling for 30 days. On May 26, 2019, Memorial Day weekend, the 2016 Federal regulations for state authorization and distance education disclosures became effective. WCET and SAN shared with institutions that if they are following SARA requirements for disclosures that they are well on their way to compliance. The Department filed a notice of appeal of the U.S. District Court ruling on June 24, 2019.

The session will provide the final chapter of Federal Regulations Groundhog Day and sort out the responsibilities of the institution for Federal state authorization regulation compliance while also providing reminders regarding state and SARA compliance.

The Online Learning Consortium, one of 12 partner organizations in the Every Learner Everywhere Network, has been tasked with researching and implementing digital learning innovations as part of the greater network goal; to provide advice, training, and community-vetted resources that support the adoption and implementation of adaptive courseware, with a focus on increasing the success of first-generation students, low-income students, and students of color (www.everylearnereverywhere.org).

In year one the ELE Digital Innovations Working Group led by OLC selected Tanya Joosten, University of Wisconsin-Milwaukee to perform an environmental scan. Tanya Joosten, Ph.D., is a Senior Scientist, the Director of Digital Learning Research and Development, and co-PI and co-Director of the National Research Center for Distance Education and Technological Advancements (DETA) at the University of Wisconsin-Milwaukee. She is nationally recognized in her work in blended and online learning as an Online Learning Consortium (OLC) Fellow and works to guide strategic digital learning efforts on campus, across the UW System, and nationally as an advisor to the Provost, a member of the University of Wisconsin System Learning Technology Executive Council, and a member of several national boards and committees (https://uwm.edu/deta/tanya-joosten/).

The purpose of this cross-institutional, qualitative research study was to better understand the profile of emerging digital learning technologies across postsecondary institutions via an environmental scan of past award submission data; specifically, looking to identify new and emerging trends to enhance educational experience and improve completion rates for high-risk populations through digital and adaptive learning. The scope of this work is to review DLIA submissions historically to identify trends within the digital innovations and adaptive learning technologies areas such as VR/AR, mobile applications, interoperability, embedded formative assessment, analytics innovation, competency credentialing, augmented mobile learning and culturally responsive technologies or other areas of focus as appropriate that can generate white papers/research, webinars, conference presentations, stories and pilot planning.

Data was analyzed throughout data collection using an inductive analytical approach and incorporated many of the procedures of the constant comparative method. More specifically, the data analysis process consisted of six steps. First, applicant identifying information was removed from the text. Second, the data was organized into one document based on area of innovation. Third, the data was coded. Fourth, researchers analyzed the codes to identify themes in each area of impact. Fifth, researchers compared coding to further distill the themes. Sixth, research cross-cut the data and identified themes based on digital learning trends. Quality control measures included member checks and peer reviews (Lincoln & Guba, 1985) to assure the validity of the findings.

The resulting data provided areas of focus for innovative adaptive learning technologies that the Every Learner Everywhere Digital Learning Innovations Working group determined through a polling process. Future work within core trends will follow a multi-phased method to select projects submitted through a peer-reviewed proposal, develop pilot plans, and advance innovative projects through the Every Learner Everywhere Network arms as a project pilot until an asset has been created and can be utilized through the Every Learner Everywhere Network or among institutions.

At the conclusion of the successful ACAO Digital Fellows Project in June 2019, we reviewed the findings of a project that included 32 chief academic Officers, 84 courses, 103 faculty members and 7,500 students across the country. The 32 of us who are Provosts and Chief Academic Officers launched campus projects that were completed using adaptive digital courseware in piloted courses on their campuses. Most of the Digital Fellows experiences anywhere from modest to significant success with their pilot projects as measured by course retention, reduced DWFI rates, and other metrics. But did the provost need to lead the project, or could someone else have stepped in? This article seeks to identify the advantages of having the Provost lead digital transformation on their campuses.

Here is what we found:

• Faculty engagement with digital learning is key, and they are more willing to follow the lead of the CAO than his/her direct reports or the CIO and his/her direct reports.
• CAOs use transformational change management to create change if they view digital learning as one of their strategic priorities and get these priorities into the university wide budget.
• CIOs become more engaged in the educational mission of the institution when partnering with the CAOs. Partnerships develop between the CIOs and the CAOs when the CAO leads this process.
• Whether or not the initial pilot program scales depends on the leadership of the CAO in the change management process.
• Data from the projects needs to be analyzed by the Chief Academic Officer and Institutional Research. Leadership from the Provost’s Office gets the attention of the President. Initiatives and funding are provided, which would not have happened without the intervention of the CAO.
• Most importantly, the ACAO project identified the importance of bringing digital learning to the attention of the CAO when that person may not have been aware of its potential.

Technologies like sensors, robotics, 3D printing and artificial intelligence are ushering in what many refer to as a Fourth Industrial Revolution, remaking industries from transportation to telecommunication and accelerating the pace of invention. At the same time, educational institutions face increasing pressure to prove a return on investment for students. At Georgia State, our goal is to ensure all our students are prepared to fully participate in the world of the future while equipping them with the real-world skills needed to enter the workplace of today. 

With this goal in mind, we’re providing students experiential learning at many levels. We’ve developed curriculum to enable students to become more digitally literate, attain career-readiness competencies and meet their career goals. We’ve worked directly with the local business, education, government and nonprofit communities to develop experiential learning programs through which our students not only learn to apply high-demand professional skills but are encouraged to become agents of change. And, as we’ve grown our experiential learning focus, the university has adopted a campuswide Quality Enhancement Plan (QEP) with a college-to-career focus. 

Several years ago, we started a digital literacy initiative, working with faculty to incorporate digital competencies into class activities in the university’s core curriculum while asking students to solve real-world problems using increasingly common digital tools across fields. For instance, students learned to write and format blogs using web scripting in an English composition course and learned to create visualizations showing the impact of an event on varying demographics in a world history class. In addition, we adopted curricular changes like working with our career services office to create a rubric that online and in-person instructors can use to measure their courses and programs toward helping students achieve the National Association of Colleges and Employers (NACE) career-readiness competencies. 

A key outcome of our curriculum changes has been that participating students asked for help continuing to develop their skills outside of class through entrepreneurial and professional activities like participation in the growing Atlanta hackathon community. As a result, we sponsored a student organization, PantherHackers, which attracted students from not only majors like computer science and information systems but also English, marketing, design and many others. Teams from this student organization won prizes in local hackathons and built a strong peer-learning community, hosting campuswide workshops on digital concepts such as programming and blockchain, and teaching soft skills such as building a team and delivering a business pitch. As the organization grew to over 400 members, their events routinely filled and they developed a strong online presence through digital collaboration tools. 

The skills students gained from participating in cross-disciplinary project teams and peer-led trainings spurred us to create more formal co-curricular, experiential learning programs that could take elements of this success and structure the process to leverage deliberate connections between industry and higher education, while giving students from all backgrounds broader access to the latest technologies and helping them gain sought-after twenty-first century workplace skills. 

Our Digital Learners to Leaders (DLL) program, for example, engages students in exploring solutions to real-world challenges using digitization, the Internet of Things, online collaboration tools and more. Participants from across majors learn the skills that are becoming more valuable in today’s rapidly changing digital economy ranging from coding and computational thinking to entrepreneurship, project management and communication, directly from industry professionals as they collaboratively develop digital solutions. The program is designed to make available to all students the tools and skills that are becoming more valuable in today’s rapidly changing digital economy, while helping provide exposure to professional pathways. DLL tackles preparing a diverse student body, both demographically and academically, for this new digital landscape by bringing together students from across majors and professionals from across disciplines to empower students to solve problems in their local community using technology. 

DLL participants have used tools such as IoT, artificial intelligence, virtual/augmented reality development tools and more to create prototypes of solutions such as a gamified recycling system using digital collection machines that lets participants earn points for recycling and apps that do everything from organize task management to teach financial responsibility to combat food waste through shared recipes and donation. 

As we look at the next phase of implementing lessons we’ve learned, we are exploring ways to continue to integrate experiential learning components into the university’s for-credit classes. To do this, we’re bringing our DLL model into a for-credit format. Further, in addition to our collegewide College-To-Career QEP, we’re developing a number of program offerings that help students build their portfolio with real-world projects and skills. Examples include a first-year, cross-disciplinary course called EPIC that is based on an experiential, project-based, interdisciplinary curriculum, as well as Project Labs that allow undergraduate students to work with graduate students and industry and community professionals across semesters using real-world tools outside of class to solve complex problems. Additionally, our instructors are using new methods to build and envision their courses, such as developing student personas that focus on determining what our students are looking to accomplish with their careers both academically and outside of class so that we can tailor our programs to meet specific student needs. 

With each implementation of experiential learning programs and curriculum, we are rewarded by seeing many students reach new levels of professional potential—and we’re learning new practices that can be applied to help all of our students obtain the digital and professional skills necessary to fully participate in and influence the world of the future. Our students have gone on to intern and work at prominent local Atlanta employers such as Coca Cola and NCR, and nationally known brands known for innovation, such as the investment firm BlackRock. Students have also found a passion for new fields of study, placed at local hackathons and taken their ideas forward to continue to make them a reality. 

Our OLC session will engage participants in making cross-organizational connections to explore elements of successful experiential learning. We will describe Georgia State’s methodology, demonstrate outcomes related to students’ professional growth and aggregate research on effective experiential learning that makes available to all students the tools and skills that are becoming more valuable in an increasingly digital workplace. The session will encourage participants to connect and share information while our programs and curriculum are provided as examples for discussion and progression.

A panel of pioneers in online learning will reflect on the last 25 years and how online learning has evolved in a quarter century. Panelists will discuss the ways in which the Sloan Consortium (which became OLC) supported the early development of online learning and online learning research, as well as how online learning has changed as it moved from the margins of higher education to its center. Special attention will be paid to how that history made online learning in the US what it is today and what it might mean for the future. Audience participation will be encouraged.

In 1992, the Alfred P. Sloan Foundation established the Anytime, Anyplace Learning Program to explore educational alternatives for people who wanted to pursue higher education but who could not easily attend regularly scheduled college classes. At the time, small numbers of motivated individuals studied by themselves away from university centers through distance education, whose pedagogies involved little or no human interaction. In 1992, the Internet was not accessible to most people, and the digital education resources that did exist could usually only be accessed at terminals on university campuses.

None-the-less, Ralph Gomory (who was then President of the Sloan Foundation) and Frank Mayadas (whom Ralph tapped to lead the Anytime, Anyplace Learning Program) believed in the capacity of computer networks to support interaction among students and instructors separated by time and distance. They called such networks “Asynchronous Learning Networks” or ALNs. Mayadas (1997, p.2) wrote, “In an ALN we can think of every person on the network as both a user and a resource. This concept is crucial to the power of an ALN, making it not just an electronic network but a network of people — an interactive learning community that is not limited by time, place or the constraints of a classroom.”

And Gomory and Mayadas set about to prove it by funding experimental classes and programs that were delivered online. Most importantly, they insisted that the quality of classes offered online should be at least as good as comparable classes offered in face-to-face settings, which to their minds meant they should be interactive. The importance of this approach cannot be overstated as it is arguably what has distinguished online learning in the United States.

As time went on, institutions who received funding as part of the Anytime, Anyplace Learning Program were brought together informally to share ideas and strategies. They met for the first time 25 years ago and that meeting grew into the conference we know today as Accelerate.

Starting in 1992, the Sloan Foundation funded 346 projects totaling $72,000,000, most of which went to non-profit colleges and universities. Major distance and adult learning providers such as the University of Maryland University College and the Penn State World Campus were early grantees. Following on the heels of these institutions, large mainstream public university systems such as the University of Illinois, the University of Massachusetts, and the University of Central Florida developed substantial online learning programs. A good example of such a program Consortium was the SUNY Learning Network (known today as SUNY Online) which was led by Eric Fredericksen and brought online learning to the 64 institutions in the State University of New York system.

Perhaps the most significant initiative of the grant program was the establishment of the Sloan Consortium of Colleges and Universities (Sloan-C). Originally an informal organization of Foundation grantees, the Consortium incorporated in 2008 as a non-profit, 501 (c) (3) organization. Sloan-C became the largest recipient of funding from the Anytime, Anyplace, Learning Program, receiving in excess of $15 million over the course of the grant program.

The Sloan Foundation continued to fund classes and programs, but also funded research on online learning and supported the dissemination of online learning research through the Sloan Consortium’s conferences and the first journal concerned solely with online learning, the Journal of Asynchronous Learning Networks (Online Learning today). In the early 2000s, large urban universities in New York, Chicago and Milwaukee were funded to develop and expand blended learning environments and the Consortium developed a Blended Learning Conference under the leadership of Mary Niemiec to bring together educators exploring the efficacy of that delivery model.

In 2014, as a self-sustaining worldwide organization, the Sloan Consortium rebranded as the Online Learning Consortium (OLC) to better align with our mission, a dedication to providing access to high quality online education to individuals, institutions, professional societies and the corporate community. A good example of that dedication to quality is the Quality Scorecard Suite. The original Quality Scorecard, created by Kaye Shelton, was designed to help institutions determine the strengths and weaknesses of their programs, and initiate planning efforts towards areas of improvement. It has been used by over 400 institutions and translated into Spanish.

The story of Sloan-C/OLC will be told by five people who played important parts in its history. Panelists will also be asked to reflect on how the organization affected the evolution of online learning in the US and how they believe it will continue to affect online learning in the future. Audience participation will be encouraged through questions to the audience and prizes for correct answers as well as time for audience questions to the panelists.

For institutions that want to create an equity initiative to support online learners, there are not many resources to support their efforts. Further, while there are various research studies that outline how individual equity issues contribute to achievement gaps in student persistence or success rates, we could find no models to address equity for online learners. That’s what led our group to create the Peralta Equity Rubric.

When we presented version 1 of the Peralta Equity Rubric at OLC Accelerate 2018, we envisioned that our rubric would support both a) faculty and instructional designers at the course level and b) staff in technology support and student services roles who serve online learners at the institutional level. Since then, we have revised the rubric and expanded the work to become the Peralta Equity Initiative.

To start, the ratings descriptions for the Peralta Equity Rubric 2.0 criteria are tighter, reorganized, and now include social belonging. [Note: we will briefly outline Peralta’s efforts to validate the rubric instruments through research.] Next, we split the rubric to support stakeholders working with online learners at the course and institutional levels. Then, for both of the new rubrics we created training modules for their respective intended audiences. Through these modules, anyone who supports online learners will a) describe the relevant factor(s) behind each equity issue (rubric criterion), b) identify strategies to address each equity issue, c) review examples of these equity strategies in action, and d) gain access to resources to put each equity strategy into practice. Last, we have assembled documentation to support your institution in starting its own equity initiative!

In this session you will discuss the equity rubric criteria, strategies to address equity and achievement gaps, and your institution’s current and planned efforts related to increase equity for online learners.

Educational innovation requires research to systematically evaluate the effectiveness of new methods of learning design and delivery. In 1991, Boyer defined the scholarship of teaching and learning (SOTL) as the systematic study of the processes of teaching and learning. Shulman (1999) further distinguished SOTL as work that is made public, available for peer review and critique, and that other peers may build upon. In essence, Shulman was describing how educational researchers can contribute to a body of science on teaching and learning. Within the Online Learning Consortium (OLC), we have an opportunity to lead the science of teaching and learning with technology (SOTLT). However, in order to take this lead, we must develop a community of researchers skilled in educational research to generate evidence of effective models, frameworks, interventions, and practices for teaching and learning with technology. We must generate a body of knowledge that is public, available for critique by peers and capable of being built upon by other scholars.

We begin by designing and conducting high quality research, even from an action research perspective, to determine the effectiveness of innovations in pedagogical approaches, including innovative uses of technology. Much of our current research focuses on case examples of new and innovative approaches, but we lack sufficient data to demonstrate generalizable results to others contexts and learning environments. We need to be able to generate a larger “N” for educational research projects to move beyond pilot projects or case studies for generalizable results.

To achieve the goal of advancing a community of SOTLT scholars, faculty and instructional designers should consider research design in conjunction with the design of new courses, pedagogical approaches or technological innovations. Time, lack of knowledge of research processes and methods can inhibit the generation of evidence. Therefore, faculty and instructional designers need a streamlined process for designing effective education research projects, research protocols must be implemented in conjunction with pedagogical innovation, and structural assistance, such as an umbrella protocol for research on innovative learning design and delivery, are required to remove the barrier of time associated with education research.

Over the last 3-5 years, an increasing focus in higher education has occurred around the topics of universal design, inclusivity, accessibility, equity, and diversity of learners. The increasingly complex digital resources incorporated both within and outside of the classroom have presented challenges towards inclusivity for faculty who are striving to make their class materials accessible to all. Additionally, content development has expanded beyond the physical or even digital classroom space, with many forms of interactivity occurring in digital public spaces where little to no accessibility considerations may have been previously considered.

Recognizing gaps both in practice as well as in best practices, a pivotal and culture-changing growth point for enhancing services to all constituents was established, supported, enacted, modified, and enhanced. The presenter (who serves as both an administrator in digital learning and also faculty) will outline several distinct case examples from multiple campuses’ successful implementation of a variety of technological tools that resulted in significant positive impacts in overall accessibility of educational content in the digital space. Further, the development and support of a campus-wide faculty incentive and training program centered around digital learning best practices has laid the foundation to both shape the culture of accessibility on university-wide campus climate and also to provide metrics to assess growth in digital accessibility over time in a campus environment.

In February 2019, an article in the New York Times described a global competition that hundreds of scientists enter every two years. Referred to as the “World Cup” of biochemical research, teams of scientists tackle a biological puzzle called “the protein folding problem.” Essentially, they try to predict the three-dimensional shape of proteins in the human body, a problem that no one has ever been able to solve. Past winners have chipped away at it but a solution still eludes the scientific community. In 2018, the Critical Assessment of Structure Prediction contest was not won by academics. It was won by a team at DeepMind, the artificial intelligence (AI) lab owned by Google’s parent company, Alphabet, Incorporated. In describing DeepMind’s accomplishment, Mohammed AlQuraishi, a biologist at the Harvard Medical School, who has dedicated his career to protein research commented that he felt “a melancholy” after losing to DeepMind. “I was surprised and deflated. They were way out in front of everyone else.” He criticized big pharmaceutical companies like Merck and Novartis, as well as his academic community, for not keeping pace. “The smartest and most ambitious researchers wanting to work on protein structure will look to DeepMind for opportunities” (AlQuraishi, 2018). He urged the life-sciences community to shift their attention toward the kind of AI work practiced by DeepMind.

DeepMind’s victory predicted the future of biochemical research, increasingly driven by machines and the people who oversee the machines. Another researcher, Derek Lowe said “It is not that machines are going to replace chemists. It’s that the chemists who use machines will replace those that don’t” (Metz, February 5, 2019).

AI development of this magnitude requires enormous amounts of data. DeepMind can lean on the massive computer data centers that underpin Google as well as many of the world’s top AI researchers who know how to get the most out of these facilities. “It allows us to be much more creative, to try many more ideas, often in parallel,” said Demis Hassabis, the chief executive and a co-founder of DeepMind (Metz, February 5, 2019). Universities and big pharmaceutical companies are unlikely to match these resources.

Kai-Fu Lee, a former senior executive at Google and Microsoft, stated that humanity is moving towards the establishment of a “new world order” dominated by AI, cloud computing and robotics (Lee, 2018) that will have significant ramifications for many aspects of human endeavors. How will our species respond? Lee believes that many workers will experience a “psychological loss of purpose” as AI changes the nature of their occupations (Lee, 2018, p. 21). A more pessimistic prediction comes from Yuval Noah Harari, bestselling author of Sapiens, who commented that AI has the potential to create a “useless class of superfluous people” (Harari, 2017, p.322). The term ““useless class of superfluous people” surely attracts attention but it may be a bit too extreme. In a later book, Harari takes a more moderate stand and discusses at length the merging of workers with large-scale integrated digital networks (Harari, 2018, p. 22). There are no firm estimates of the number of jobs in this country that will be displaced by AI and other forms of automation. While one estimate suggests 47 percent (Frey & Osborne, 2013), another poses 38 percent (Berriman & Hawksworth, 2017), and yet another puts it as low as 9 percent (Artnz, Gregory, & Zierahn, 2016). The fact is that no one really knows. One aspect of this displacement is certain, and that is that many of these displaced jobs will be in white collar and professional areas such as teaching, law, and medicine as well as the corporate sector.

The purpose of this session will be to speculate specifically on the future of higher education as online technology, such as AI infused adaptive software and analytics, changes the traditional role of educators in our colleges and universities. Online and adaptive learning have already advanced within the academy, but the most significant changes are yet to come. This session is meant to complement another session examining the role that online education has played over the past twenty-five years.

Session Learning Objectives (3)

• Illustrate the implementation of adaptive and active learning in open scale courses.
• Describe current efforts to develop courses that support personalized instruction at scale.
• Demonstrate innovative technology that reinforces student engagement and success.

Takeaways for Session Attendees

This session will showcase adaptive assessment tools incorporated into Open Scale Courseware (OSC) at Arizona State University (ASU), provide course outcomes (student success) and showcase technical solutions for learning. Takeaways include a proven implementation model, outcomes and experiences representing multiple perspectives, and a scalable solution for achieving student success.

Introduction

Everyone is busy! This is particularly true for today’s adult learners who often need to juggle many responsibilities, including a job, family obligations, and other life commitments. Fulfilling these obligations, however, comes often at the cost of professional career advancement where additional education credentials are required. Today’s adult learners simply cannot disregard their responsibilities to take time off for pursuing the necessary formal education in a traditional campus experience.

One possible solution is the enrollment in online programs offered through accredited universities. In their latest review on the status of online education in the US, Allen and Seaman (2018) stated that enrollment in online courses has been consistently increasing over the past decade with more than 6.3 million learners taking classes in 2016. Although online education offers flexibility for busy adult learners, most universities still set rigorous admission standards often coupled with significant tuition expenses. Meeting these admission standards or costs is particularly a barrier for those learners who previously struggled in their academic experiences or barely earn enough income to make ends meet.

Here, Arizona State University’s (ASU) Open Scale Courseware (OSC) offers another alternative to attain an education. Similar to existing Massive Open Online Courses (MOOCs), the OSC platform or website is powered by Open edX and offers users access to first-year online university courses developed by ASU and taught by ASU faculty and instructional teams. In contrast to MOOCs, these courses may be taken either for auditing purposes or in pursuit of transferable university credit. Auditing allows users to explore courses without any option to earn credit or obtain any verified record of participation. In order to gain and maintain eligibility to opt for ASU credit, users must adhere to all associated rules and guidelines governing course participation, academic integrity, academic performance, fees/payments, and credit conversion.

ASU also offers students who were previously denied admission a way to earn conditional entrance into the university. This new opportunity allows learners to successfully complete a series of online courses that count toward their degree. This program is a perfect demonstration of ASU’s charter to include and support all learners and their academic goals.

Engaging Busy Adult Learners in OSC

Engaging adult learners is particularly challenging in MOOCs where completion and retention rates are often very low (Jordan, 2015). Reviewing the completion rates of over 200 MOOCs between, Jordan showed that completion rates “vary from 0.7% to 52.1%, with a median value of 12.6%” (p. 341). These low numbers are concerning because effective and efficient online learning generally requires consistent engagement in the learning experience.

To better engage adult learners in OSC, Instructional Designers at ASU sought to integrate established cognitive science principles in their online teaching and learning strategies. In their meta-literature review on applying cognitive science principles to create effective, efficient, and engaging online learning experience, Nilson and Goodson (2017) suggested 25 universal strategies for designing, organizing, and presenting online courses. In particular, ASU’s OSC courses were designed where (1) students learn from constant practice and targeted feedback; (2) students learn best in a low-stress and anxiety-free environment; and (3) students learn better when they review materials multiple times in intervals throughout the course. These three principles “focus on how students receive … content… [as well as] drive and sustain the whole process of learning” (p. 79).

Applying Cognitive Science Principles

To implement these three strategies, ASU partnered with companies that offered scalable learning tools, such as Cerego and InScribe. These tools use a combination of artificial intelligence, machine learning, and adaptive technology to provide immediate, personalized feedback and practice to improve memory skills and cognition.

InScribe is a community of learners and educators that work together to provide highly scalable, context specific support. It uses this power of community and artificial intelligence to connect students to the most relevant resources, answers, and individuals they need to succeed in school and beyond. InScribe then captures these valuable interactions, and makes them reusable, so each generation of students benefits from the conversations that came before them.

Then, InScribe A.I. analyzes student interactions, proactively escalating high priority issues and students that require direct intervention. Ultimately, experts spend less time in email and discussion forums, and more time with the students that need help most.

We implemented Inscribe using learning tool interoperability (LTI) on a standalone page that replaces the Open edX discussion board. This unique learning community provides myriad resources to the students further enhancing learning and retention that can be added by the student or the faculty. Having this robust knowledge base allows the course to evolve and stay current without major revisions, thus saving time and money. The option to directly communicate with the moderators provides seamless communication and privacy when necessary. Furthermore, Inscribe also has an upvoting feature to assist students in finding the most relevant resources and encourages positive community interactions. Overall, we have found Inscribe to be a valuable community resource for our students.

ASU currently uses Cerego in nine of our OSC courses, ranging from engineering, marketing as well as social science courses. In each of these subjects, learners demonstrate content mastery either through a web browser, a mobile application, or a digital assistance. All options are is seamlessly integrated either through mobile app or with Open edX through learning tool interoperability (LTI) and in-frame interaction with grade passback. It uses the principles of neuroscience and cognitive science to provide a personalized learning experience, even on-the-go. For example, using the Cerego app, learners can quiz themselves on vocabulary for a Microeconomics course, star patterns in Astronomy, or Excel formulas in a computer applications course. It implements the evidence-supported cognitive science algorithms and intelligent system optimization to deliver the right instructional and quiz content to users at the perfect time to boost retention and engagement. Furthermore, the machine-learning approach constantly adapts, which allows for user-by-user, item-by-item personalization. Feedback has shown that students want a more personalized experience, which is exactly what Cerego is proposing to do.

When comparing students who completed only some memory sets vs. those who have completed all sets, there is a noticeable 10% average difference on the final grade. Student feedback regarding this tool is overwhelmingly positive, e.g., “Cerego is most likely key in retention of concepts and an excellent learning tool” and “[Cerego] took me from having basic knowledge to solidifying my mastery of each section very quickly.” The staff and faculty share the same positive thoughts for the product as the students. They have access to analytics that focus on missed questions, time in a set, etc. that guides the faculty to a better course experience for the students. Cerego has proven to provide an effective and personalized learning experience for all our busy learners.

Conclusion

ASU is continuously taking strides in finding innovative tools to support student learning. By partnering with these tools, ASU has created a personalized learning experience that can be utilized when the student has a free moment to study. In this session, we will demonstrate how these affordances are implemented in ASU’s OSC courses and, as a result, have shown to engage busy adult learners.

Since the 1980s, there has been a growing body of literature and research that recognizes the importance of Learning Sciences (LS). Learning Sciences seek to embody a multidisciplinary approach that is aligned with the constructivist, social-constructivist, socio-cognitive, and socio-cultural theories of learning. Applying this multidisciplinary approach to learning is a shift from the traditional methods which predominantly focused on grades and qualifications. While degrees and qualifications are essential, LS goes beyond the conventional methods by considering “… knowledge, skills, and abilities that are not yet measured well by commonplace test scores nor yet signified by established credentials” (Rochelle et al. 2014). The overall aims of learning science are “…to understand the nature of learning from a broad range of perspectives, and to shape the ways that are learning environments and resources are designed and used”(Nathan and Alibali 2010, p.10).

Learning sciences will transform the way learning is perceived. This presentation has three main objectives (1) to articulate the need for an interdisciplinary approach for learning via learning sciences, (2) to analyze the requirements for learning environments for the 21st century within a learning sciences framework, and (3) to present a multidisciplinary approach for course design and development.

During this interactive and informative session, the presenters will:

• Share and discuss current thoughts, developments, and positions on learning sciences.
• Share with the audience an approach for developing a framework for course design and development
• Articulate the principles of design-based research used by researchers with an interest in learning sciences.

Reference Nathan, M. J., & Alibali, M. W. (2010, 05). Learning sciences. Wiley Interdisciplinary Reviews: Cognitive Science, 1(3), 329-345. doi:10.1002/wcs.54

Roschelle, J., Grover, S., & Kolodner, J. (2014). CIRCL Primer: Learning Sciences. In CIRCL Primer Series. Retrieved from http://circlcenter.org/learning-sciences/

As academic technologies mature and are more deeply integrated into higher education, significant ‘data exhaust’ from student and faculty use of these applications provides a rich set of behavioral data that was not previously available. Over the past decade, data science techniques have been applied to to this data and have generated surprising insights. What are some of the most promising results that we’ve seen from this work? What ethical implications are created for institutions, faculty, and practitioners involved in this work?

In this presentation, we will discuss the state of the field from the perspective of a data science leader directing this work and an academic technology leader planning and implementing this work on his campus. We will provide a brief overview of the field then discuss several studies and deployments of learning analytics that we have collaborated on and/or led from our respective roles.

The studies that we will discuss include:

a. Stealth Assessment of Social and Emotional Skills using Learning Analytics – current work in progress (results September 2019) to evaluate the relationship between social and emotional skills and online activity (LMS and e-Textbook). Will investigate “learning patterns” using sequential data mining instead of aggregate count analysis, and also use deep learning and advanced techniques. This study could provide insights into the relationship between constructs such as “grit”, “tenacity”, “curiosity” and student online activity.

b. Student Course Intervention Analytics – discuss multiple current projects underway at UMBC to predict student performance early in the term and make interventions to improve their outcomes. Using multiple solutions and systems (BB Predict, EAB, Civitas) we can compare predictive accuracy, the intervention lifecycle, and the impact on student success.

c. Automated Writing Evaluation – discuss how natural language processing systems are being used in practice to augment faculty decision-making. We will review the process of “training” the models used for evaluation and the research students that are used to ensure that automated grades are accurate representations of faculty assessment.

We will also discuss ethical considerations that emerge from this work. Recent discussions, especially those informed by the European Union GDPR framework, have focused on the rights of students and the importance of technology companies and academic institutions in clearly describing how data is being used and providing students with a “right to be forgotten” and remove themselves from data analysis. In addition to these concerns, we will discuss the potential damage to students from not implementing analytics, which John P. Campbell called “the ethical obligation of knowing”. Given the potential insights that can be gleaned from this data, what are the ethical responsibilities of institutions to create insights from this data?

We will conclude the session with an open question and answer session for participants to provide feedback, present their questions, and talk about how these issues are related to their work in online education.

Campbell, J. P. (2012). Obligations of Knowing: Ethics of Data Collection and Analytics. In Educause ELI 2012 Online Spring Focus Session: Learning Analytics. Retrieved from http://www.educause.edu/ELI124/Program/GS07 on April 11, 2012.

This session describe the emerging field of learning engineering, to show some of the different models of learning engineering that have emerged, and and to consider the many opportunities that learning engineering may offer to the ongoing professionalization of instructional design and development. We believe that the partnership between IDs and learning engineers is one of the essential first steps for integrating learning engineering methodologies into educational practice, and could think of no better place to bring our early work for review and consideration by ID peers.

The term “learning engineering” was coined 50 years ago by Herbert A. Simon while at Carnegie Mellon, who saw the essential benefits of applying technical competencies to learning design. Today, Simon’s vision is evident as learning engineering emerges as both a professional practice and an academic discipline. Today’s learning engineering is framed as the application of engineering methodologies in developing learning technologies and infrastructures to support learners and learning. We will explore the opportunities, challenges, and essential collaborations required to realize full benefits of this emerging discipline.

Session Outcomes: * Explore what learning engineering is, what it does, how it differs from ID and why they both matter * Contribute important educational perspectives to the value of creating a new discipline for driving greater value in learning tech * Discuss strategies for assembling effective “learning tech teams” including learning engineering and ID.