D293 - Assessment and Learning Analytics - Section 2: Determining Learning Analytics Strategy - Lesson 1: The Purpose of Learning Analytics

By developing student awareness to support self-reflection How can learning analytics be used to encourage student success? True Sharing learning analytics dashboards with students provides a basis for self-reflection. Descriptive Which type of learning analytics should a learning experience designer begin with as a first step toward optimizing learning in K-12, higher education, and workforce development? True Descriptive analytics is the easiest learning analytics type to implement. It describes existing patterns of learning and shows where improvements can be made, which is the first step in optimizing learning. True Predictive analytics builds on diagnostic analytics to forecast future or otherwise unknown events. An example of this is a learning management system that shows students how much time was used to complete work and how much time should be set aside for future work. True Prescriptive analytics is the most complex type of learning analytics to implement. It looks back at prior performance in order to recommend future actions. For example, for a learner who has consistently struggled in a business math course, prescriptive analytics may recommend completing an algebra review before moving forward. True Diagnostic analytics is a form of advanced analytics that examines data or content to identify why something happened. Diagnostic analytics is used after descriptive insights have been analyzed. True Learning analytics supports quality learning and teaching by providing empirical evidence of the success of pedagogical innovations but does not standardize teaching practices. Descriptive The teacher has gathered the learning data of a fifth-grade world history class throughout an entire school year. The school seeks a 10 percent improvement in student learning and wants to use the data from this year as a benchmark for comparison to students who take history next year. The school principal has asked the teacher to use the data to establish learning growth benchmarks based on the current year's data. To establish the desired benchmark, _____________ analytics should be used. For the past five years, the number of students reading at grade level has declined. The school would like to know what actions should be taken to break the five-year decline in the number of students reading at grade level. Which scenario is an example of how prescriptive analytics can be used in a K-12 setting? True Diagnostic analytics helps answer questions about why things happen. This type could be used to figure out why one year was more successful than another, but it does not establish benchmarks. True Predictive analytics is used to determine what may happen in the future. After many years of data has been collected, this type could be used to predict a new benchmark. True Prescriptive analytics helps discover what should be done. This type may be used to figure out how to improve student learning but does not help establish benchmarks. True The key factors that motivate investment in learning analytics are student retention, course-level academic success, and reduced time to degree. Reducing costs and optimizing institutional resources are second-tier factors for investment. True Institutions more commonly use learning analytics data to monitor or measure student progress than to predict success or prescribe intervention strategies. The latter activities are indicators of true learning analytics, while the former are conventional best practices of using data and information in traditional ways to inform decisions. True Major challenges to embedding the use of learning analytics into institutional practices include data-quality concerns, system integration difficulties, lack of support of key leadership, and a possible faculty culture of resistance. True Learning analytics outcomes are difficult to assess due to the lag time required to measure the results of analytics-triggered interventions.