Design and Development Research: Deploying Adaptive Learning Environments to Overcome Background Deficiencies and Facilitate Mastery of Computer Engineering Content

设计和开发研究：部署自适应学习环境以克服背景缺陷并促进对计算机工程内容的掌握

• 批准号: 1432373
• 负责人: Brock LaMeres
• 金额: $ 29.81万
• 依托单位: Montana State University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2015
• 资助国家: 美国
• 起止时间: 2015-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1432373&HistoricalAwards=false
• 关键词: Design; Development; Research; Deploying; Adaptive

Many students who intend to major in computer engineering do not persist through the introductory sequence of digital logic courses that are part of every accredited computer engineering program in the U.S. These students often lack the necessary prerequisite knowledge due to their varied backgrounds and incoming preparedness levels. This problem is compounded by the large class sizes of introductory college courses, which make it difficult to accommodate the background knowledge and the skills of individual students. Additionally, an e-learning environment has the potential to reach a broad audience through remote delivery, thus further increasing the impact of this approach. This enables community colleges and 4-year universities to move toward a true two-plus-two transfer program by allowing students to complete lower-level computer engineering courses remotely before transferring. The adaptive learning materials in this project will be developed for use in an introductory digital circuits course and a logic design course. Both of these courses contain laboratory components that will also be addressed by this work. The materials will be developed as self-contained learning modules that can be used at different colleges with varying schedules (e.g., semester vs. quarter). The materials will consist of a unified, adaptive learning environment that can be implemented using any course management system (e.g., Moodle, Desire2Learn, Blackboard) to eliminate the need for proprietary software. An accompanying lab kit will facilitate hands-on learning in a low-cost, portable form factor to facilitate remote delivery and eliminate the financial barrier of offering a meaningful laboratory experience. The materials will be tested at a diverse set of institutions: Montana State University, a Ph.D. granting, research active university, MSU-Billings, a 4-year non-research university, Flathead Valley Community Colleges, the largest 2-year community college in Montana, and Salish Kootenai College, a Tribal College proving both 2-year and 4-year degrees for Native Americans. This broad range of participants will allow the team to assess the effectiveness of the adaptive learning materials while simultaneously considering the relationship between student background and the student learning experience. Both quantitative and qualitative measures will be used to assess the adaptive learning modules. Direct measures will be collected on student performance, including the number of ungraded quiz attempts within an adaptive module, end of module exam scores, time required to complete a module, and time spent at each level of difficulty within a module. Surveys will be used to collect student satisfaction with the adaptive learning environment that will include feedback on their impression of content difficulty, workload compared to other courses of the same credit load, and their sense of how well the material was personalized to their needs. Student demographic information will be collected including gender, ethnicity, age, socioeconomic background, ACT scores and college credits obtained. This information will be used to understand how different groups use and benefit from the course materials. Focus groups will also be conducted with student participants at Michigan State University in order to collect qualitative data on student learning and attitudes toward the e-learning system. Phone interviews will be conducted with students from the other participating institutions. The interim findings from this assessment will be used as feedback to enhance the adaptive learning system in order to accommodate a broader range of participants.

许多打算专业的计算机工程专业的学生并不是通过数字逻辑课程的入门顺序持续存在的，这些课程是美国每个认可的计算机工程计划的一部分，这些学生通常由于背景和入学准备水平而缺乏必要的先决条件知识。大量的学院课程使这个问题更加复杂，这使得很难适应个人学生的背景知识和技能。此外，电子学习环境有可能通过远程交付吸引广泛的受众，从而进一步增加了这种方法的影响。这使社区学院和4年的大学能够通过允许学生在转学前远程完成远程计算机工程课程，从而朝着真正的两人两次转会计划迈进。该项目中的自适应学习材料将用于用于入门数字电路课程和逻辑设计课程。这两个课程都包含实验室组件，这项工作也将解决。这些材料将作为独立的学习模块开发，可以在不同的大学（例如，学期vs. Quarter）中使用。这些材料将由一个统一的自适应学习环境组成，可以使用任何课程管理系统（例如Moodle，Desire2Learn，Blackboard）来实施，以消除对专有软件的需求。随附的实验室套件将促进在低成本的便携式外形方面促进动手学习，以促进远程交付，并消除提供有意义的实验室体验的财务障碍。 这些材料将在各种机构中进行测试：蒙大拿州立大学，博士学位。授予研究活跃大学，MSU BILLINGS，一所4年的非研究大学，Flathead Valley社区学院，蒙大拿州最大的2年社区学院以及Salish Kootenai College，这是一所部落学院，证明了美国原住民的2年和4年学位。广泛的参与者将使团队能够评估自适应学习材料的有效性，同时考虑学生背景与学生学习经验之间的关系。定量和定性措施都将用于评估自适应学习模块。将收集有关学生绩效的直接措施，包括自适应模块中未分级的测验尝试的数量，模块考试得分的结尾，完成模块所需的时间以及在模块中的每个难度级别上花费的时间。调查将用于收集学生对自适应学习环境的满意度，其中包括对内容难度的印象，工作量的反馈，与其他信贷负载的其他课程相比，工作量以及对材料对他们需求的个性化程度的感觉。将收集学生人口统计信息，包括性别，种族，年龄，社会经济背景，ACT分数和获得的大学学分。该信息将用于了解不同的群体如何使用和受益于课程材料。焦点小组还将与密歇根州立大学的学生参与者一起进行，以收集有关学生学习和对电子学习系统的态度的定性数据。电话访谈将与其他参与机构的学生进行。该评估的临时发现将被用作反馈，以增强自适应学习系统，以适应更广泛的参与者。