Educause

Games are no longer just for fun; they offer potentially powerful learning environments. Today's students have grown up with computer games. In addition, their constant exposure to the Internet and other digital media has shaped how they receive information and how they learn. There are many attributes of games that make them pedagogically sound learning environments. An increasing number of faculty are using games as enhancements to the traditional learning environment with encouraging results. While the interactivity and engagement of games are highly positive a number of questions remain about how games will be developed, deployed and accepted in higher education. Invited Commentary: Mason, R. (2004) Commentary on: Oblinger, D. (2004). The Next Generation of Educational Engagement. [PDF] Editors: Terry Anderson and Denise Whitelock.

Collection : Horizon Report

Collection : Horizon Report

Open source. Open access. Open society. Open knowledge. Open government. Even open food. The word “open” has been applied to a wide variety of words to create new terms, some of which make sense, and some not so much. This essay disambiguates the many meanings of the word “open” as it is used in a wide range of contexts.

In Fall 2013 we offered an open online Introduction to Recommender Systems through Coursera, while simultaneously offering a for-credit version of the course on-campus using the Coursera platform and a flipped classroom instruction model. As the goal of offering this course was to experiment with this type of instruction, we performed extensive evaluation including surveys of demographics, self-assessed skills, and learning intent; we also designed a knowledge-assessment tool specifically for the subject matter in this course, administering it before and after the course to measure learning. We also tracked students through the course, including separating out students enrolled for credit from those enrolled only for the free, open course. This article reports on our findings.

In the fall of 2013, we offered an open online Introduction to Recommender Systems through Coursera, while simultaneously offering a for-credit version of the course on-campus using the Coursera platform and a flipped classroom instruction model. As the goal of offering this course was to experiment with this type of instruction, we performed extensive evaluation including surveys of demographics, self-assessed skills, and learning intent; we also designed a knowledge-assessment tool specifically for the subject matter in this course, administering it before and after the course to measure learning, and again 5 months later to measure retention. We also tracked students through the course, including separating out students enrolled for credit from those enrolled only for the free, open course. Students had significant knowledge gains across all levels of prior knowledge and across all demographic categories. The main predictor of knowledge gain was effort expended in the course. Students also had significant knowledge retention after the course. Both of these results are limited to the sample of students who chose to complete our knowledge tests. Student completion of the course was hard to predict, with few factors contributing predictive power; the main predictor of completion was intent to complete. Students who chose a concepts-only track with hand exercises achieved the same level of knowledge of recommender systems concepts as those who chose a programming track and its added assignments, though the programming students gained additional programming knowledge. Based on the limited data we were able to gather, face-to-face students performed as well as the online-only students or better; they preferred this format to traditional lecture for reasons ranging from pure convenience to the desire to watch videos at a different pace (slower for English language learners; faster for some native English speakers). This article also includes our qualitative observations, lessons learned, and future directions.

This chapter reveals how thoughtful course redesign that specifically addresses the physical environment of a learning space can significantly improve student learning.

Alignment is defined as “the proper positioning or state of adjustment of parts, or an arrangement of groups or forces in relation to one another.” For an information technology (IT) organization, “proper positioning” within an institution becomes inherently more important as technology emerges as a common thread in collegial and institutional activities. In ever more circumstances, the actions of the institution and the IT organization affect the decisions of the other.

Abstract As online learning continues to grow, so do the free or nearly free Web 2.0 and emerging online learning technologies available to faculty and students. This chapter explores the implementation process and corresponding considerations of adapting such tools for teaching and learning. Issues addressed include copyright, intellectual property, support, and privacy.

The invention of the printing press reduced higher education’s learning-resource scarcity. Access to learning increased, and this democratization of education indirectly contributed to the idea of political democracy in the western world. As part of these political changes, equilibrium was sought between the supply of expertise needed to promote prosperity and the demand for such expertise. This equilibrium has been elusive as the world economy shifts to a reliance on intellectual capital. To complicate matters, we now live in a world of staggering information abundance. How do we mange such boundless information? One answer may lie in viewing the social character of information (how information is used) as fundamental in setting information management agendas. This article presents a holistic approach to information management as one strategy to create effective management of information that starts with the individual and ends with collective knowledge and wisdom.

Active learning classrooms (ALCs) have been demonstrated to have significant and positive impacts on student learning experiences, student learning outcomes, and instructor and student behavior compared to traditional classrooms. The social context of a classroom – levels of student–student and student–instructor interaction – has been demonstrated to partially explain the effects ALCs have on students and instructors. This research is the first attempt to extend social context research beyond the US higher education classroom by comparing levels of social context of Chinese and US students taking courses in ALCs. We find that formal student–instructor relations in the US and China are not the same, that general student–student relations, informal student–instructor relations, and students as instructors are quite similar for Chinese and US students, but that these relationships express themselves at different levels. We believe that some of the variation observed can be attributed to cultural differences but are hopeful that the similarities observed lend themselves to expanding learning space research on social context to other countries and advancing cross-cultural research on learning spaces.

Abstract In the past, technological tools were considered a “solution” to advising challenges. However, successful advising transformation efforts have also incorporated shifts in institutional culture and workforce in addition to the adoption of new technologies. Approaching advising redesign as a digital transformation (Dx) initiative can transform an institution's operations, strategic directions, and value propositions surrounding advising. This chapter articulates an approach to the implementation of advising technologies and the necessity to view “holistic advising redesign” as a Dx initiative for advising to reach its full potential at scale. For institutions, this means embracing not just the promise of new technology but also the investment in and attention to the critical shifts in culture and workforce.

Research Computing and Data is changing at an accelerating rate, while the range of fields and disciplines depending on the cyberinfrastructure is expanding and becoming increasingly diverse. This poses significant challenges to academic institutions as they try to effectively assess and plan for the necessary support infrastructure to keep pace with the needs of researchers. We present a Research Computing and Data Capabilities Model that identifies the range of relevant approaches to fully support and enable research computing and data on campuses. This model allows institutions to assess their current capabilities, and provides structured input into strategic decision making, using a shared community vocabulary. We describe the background of the Model, key concepts and features of the Model and an associated assessment tool, initial experience in the community and lessons learned, and a roadmap for further development.

Learning analytics has become a robust research area in the last decade, as innovative analytic models of learning data have been created with the goal of enhancing teaching and learning. However, barriers to large scale adoption of such technologies in higher education still exist. In recent years, a strand of research has begun to investigate stakeholders' expectations of learning analytics, hoping to find ways to integrate the innovations into everyday teaching practices. For instance, studies have investigated instructors' ideas about how learning analytics might be helpful, as well as concerns about student data privacy. However, most studies have taken a general approach rather than considering instructors' day-to-day experiences. Using survey methods, we presented instructors with hypothetical scenarios of learning analytics in use across disciplines, class sizes, teaching activities, and types of student data. We asked for ratings of both usefulness and privacy concerns for each proposed teaching situation. Our respondents considered scenarios involving learning outcomes-related data (e.g. grades) to be more useful than those that involve student interactions (e.g. language, social activity). In contrast, privacy concerns were lower for outcomes-oriented scenarios than interactions-focused scenarios. An interesting new finding was a negative correlation of usefulness and privacy; we discuss this in the context of instructors' possible cost-benefit reasoning. We reflect on our findings with respect to future efforts in developing and fielding learning analytics tools.

Purpose: The purpose of this study is to make an exploratory inquiry into the state of policy development processes in institutions of higher education, and to review the history and mission of the Association of College and University Policy Administrators (ACUPA). Methodology: Members of ACUPA were surveyed concerning their opinions of the status of policy development, and where the policy process was located in local governance structures. A survey was conducted of ACUPA membership in March and April 2005. Results: 24 institutions responded to the survey, half of them identifying themselves as Doctoral or Research Universities (Carnegie Classification, 2000). 75% of respondents rated their policy development processes as “average”, “above average”, or “very good”. 60% report to a President or Vice President. Conclusions: The results were inconclusive. There appeared to be a tendency for those who portrayed their policy process as “centralized” or “both” to rate their process more favorably than those who described their setting as “decentralized” or “disorganized.” Nearly 65% (9 of 14) of those who chose “centralized” or “both” rated their process either “very good” or “above average.” Even though this small survey sample had inconclusive results, it is a significant contribution to the literature in the field, which is scarce. Recommendations: This brief survey raised additional questions which need further research. Persons who are interested in joining the network of policy administrators and developers of ACUPA should view the web site at http://www.acupa.org/ for more information.

Abstract The United States Department of Agriculture’s National Agricultural Statistics Service (NASS) conducts the June Agricultural Survey (JAS) annually. Substantial misclassification occurs during the prescreening process and from field-estimating farm status for nonresponse and inaccessible records, resulting in a biased estimate of the number of US farms from the JAS. Here, the Annual Land Utilization Survey (ALUS) is proposed as a follow-on survey to the JAS to adjust the estimates of the number of US farms and other important variables. A three-phase survey design-based estimator is developed for the JAS-ALUS with nonresponse adjustment for the second phase (ALUS). A design-unbiased estimator of the variance is provided in explicit form.

Abstract Planning for the ongoing support and maintenance that accompany implementation of new enterprise resource planning systems may be more essential to realizing benefit from a technology investment than choosing the product with the most features.

Abstract Higher education administrators will need leadership skills appropriate to frequently disruptive but newly empowering technologies.

Appreciative inquiry is an approach with the power to contribute to inclusion in the workplace. Paired with digital interventions, which share the power to include and the potential to exclude, digital appreciative inquiry offers promising possibilities when used with intention. This chapter presents guidance to help higher education institutions accomplish the goals of inclusion using digital appreciative inquiry, which can lead to greater staff and faculty belonging, trust, engagement, and institutional sustainability.

This chapter is an argument for and celebration of lessons learned during the pandemic of 2020 toward the end of designing authentic and engaging learning experiences across education systems. In the forced shift to online and multimodal learning, educators and students experienced challenges of access, equity, and low engagement. However, there is an opportunity to extrapolate the lessons of 2020 for the betterment of education into the future. This chapter describes lessons pertaining to planning and collaboration, classroom environment, humanized online practices, as well as empowering pedagogy. The chapter concludes with three practical application examples for further thought and inspiration. The pandemic year can be one to survive and never think about again or, with the proper perspective, education's greatest learning moment.