Learning Resources

Abstract: Student success analytics promise to dramatically improve our capacity to increase student success across the entire spectrum of the student life cycle and throughout the student experience. Institutions will move beyond institutional accountability statistics to improve performance at the level of student success processes, practices, and interventions. Ultimately, these new processes, practices, and interventions promise to enable institutions to reinvent and personalize approaches to success.
By leveraging analytics and data science, leading-edge institutions “optimize” student success for individuals and cohorts by making student success a mission-critical, overarching institutional strategy. “Student success science” is a critical ingredient in reimagining higher education. This article provides a road map for institutional leaders on how to raise their analytics IQ so that they can leverage these practices to better serve their students, improve performance, and demonstrate value.
The use of analytics is potentially a key ingredient in sense making and decision making in all aspects of institutional performance and is critical in improving student success. Enlightened higher education leaders are committing to analytics and data science that deliver active interventions that improve student success.

Abstract: Many institutions of higher education develop assessment systems to demonstrate evidence of value added and to meet accreditation requirements. The sustainability of such assessment systems is usually defendant on creating a culture of assessment, which entails establishing shared values and principles and implementing practices designed to meet organizational goals. A survey of 119 assessment professionals revealed both the challenges and facilitating factors in creating and sustaining a culture of assessment. This article presents the survey results organized by an institution’s stage of development in establishing a culture of assessment: beginning, progress, or maturation. The article also provides specific examples to help institutions move along the continuum or improve their current practices and concludes with a discussion of policy implications

Abstract: The Balanced Scorecard is a planning model used extensively in business to provide direction and accountability to an organization. Despite the demonstrated success of the model, it has not been widely used in higher education. This article compares and contrasts the use of the Balanced Scorecard by two small, private colleges. The article includes examples of how the model was implemented, how it is used for cyclical improvement, and how it can be used to improve communication concerning institutional planning.

Abstract: This book provides insight on the higher education assessment process with an emphasis on planning and metrics. Using their extensive experience on the University of Delaware campus, the authors give numerous examples of the integrated nature of planning. Intended for anyone on campus who is involved with the planning or accrediting process.

Abstract: Educational technology units must continually monitor their strategic plans to ensure that they are aligned with the evolving realities of their institutions. Strategic dissonance occurs when previously successful strategies are no longer achieving the same results. This article uses the Virtual Retina project as an example of strategic dissonance for the Academic Technologies for Learning at the University of Alberta. A number of methods for analyzing the strategies used by educational technology units are presented. These methods provide a means for units within institutions of higher education to conduct the ongoing task of renewing their strategic plans.

Abstract: This article uses the results of a national study to propose several multidimensional planning models for institutional planners and researchers. It focuses on developing, supporting, and using a number of dimensions within six domains that the research study identified as important factors for inclusion in planning models. The domains are external influences on student assessment, institutional context (type, control, and size), institutional approach to student assessment, institution-wide support for student assessment, assessment management policies and practices, and uses and impacts of student assessment.

Abstract: A review of “Assessing Educational Outcomes,” by Peter T. Ewell, (ed.), New Directions for Institutional Research Issue Number 47, San Francisco: Jossey-Bass, Inc., 1985.