Using Perceptual and Adaptive Learning to Advance Chemistry Education

利用感知和适应性学习推进化学教育

• 批准号: 7942045
• 负责人: PHILIP J KELLMAN
• 金额: $ 45.86万
• 依托单位: UNIVERSITY OF CALIFORNIA LOS ANGELES
• 依托单位国家: 美国
• 财政年份: 2009
• 资助国家: 美国
• 起止时间: 2009-09-30 至 2012-02-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/7942045
• 关键词: 3-Dimensional; Address; Algorithms; Area; Base Sequence; Categories; Chemicals; Chemistry; Cognitive Science; Communities; Complex; Computer software; Control Groups; Data; Development; Education; Educational Curriculum; Educational Status; Engineering; Enrollment; Evaluation; Event; Health Sciences; Individual; Instruction; Internet; Intervention; Laboratories; Lead; Learning; Legal patent; Mathematics; Memory; Methods; Molecular Structure; Nomenclature; Occupations; Online Systems; Outcome; Participant; Pattern Recognition; Perceptual learning; Performance; Pilot Projects; Population; Process; Public Health; Randomized; Research; Science; Speed; Stream; Structure; Students; System; Talents; Technology; Testing; Update; Work; college; efficacy testing; grasp; improved; innovation; public health relevance; scale up; stem; success; time use; university student

DESCRIPTION (provided by applicant): Using Perceptual and Adaptive Learning to Advance Chemistry Education This proposal addresses broad Challenge Area 12) Science, Technology, Engineering and Mathematics Education and specific Challenge Topic 12-OD-101: Efficacy of educational approaches toward promoting STEM competencies. The work will refine and test the efficacy of Chemistry learning modules that incorporate advanced perceptual learning and adaptive learning technologies, both of which have great, but largely untapped, potential to improve STEM learning. The target learning group will be community college students taking basic chemistry courses. This student population is a large and important group, representing a considerable pool of talent for a broad spectrum of health and science-related occupations. The project seeks to address two major problems that limit student learning. One involves students' abilities to grasp and process fluently crucial structures and relations. Recent work suggests that this problem can be addressed with dramatic success by perceptual learning principles embedded in learning technology. A second problem is that learning does not adapt to the needs of the individual learner. These limitations can be overcome by the use of adaptive learning technology in which learning events are sequenced based on learner accuracy and speed. The learning interventions to be tested take the form of Perceptual Learning Modules (PLMs). PLMs accelerate, through short, interactive trials, learners' abilities to quickly and accurately process key structures and relationships in complex domains. PLMs are web-based; they deliver learning and assessment via standard browsers over the Internet; and they can be easily scaled-up for broader use. The technology will incorporate recently patented adaptive learning algorithms that use a continuous stream of performance data to optimize principles of learning and memory, producing improved efficiency of learning and assessment. The project team, consisting of experts in cognitive science, learning technology, curriculum development and evaluation, chemistry and chemistry education, will refine two previously developed Chemistry PLMs and develop one new one using existing adaptive learning software, allowing a broad test of these technologies. Both laboratory pilot studies and full-scale efficacy studies in community college Chemistry courses will be carried out. Efficacy studies will include randomization by participant; treatment groups will be compared to control groups who spend comparable amounts of time using conventional materials; and conditions that test efficacy of specific components of perceptual/adaptive learning will be included. The proposed efficacy studies are expected to yield robust learning gains, indicating the potential of perceptual learning to produce pattern recognition and fluency, and the potential of adaptive learning technologies to fit individual learning needs and produce mastery. Results will have implications for Chemistry education and learning in other STEM fields, particularly for students who struggle with traditional instructional methods. Public Health Relevance: The proposed project will test the efficacy of web-delivered perceptual and adaptive learning technologies in Chemistry learning by community college students, a large and important group that includes a majority of all students enrolled in colleges, many of whom belong to groups traditionally under-represented in STEM fields. Results obtained in this project will inform educational practice; successful outcomes could lead to widespread effective use of perceptual and adaptive learning technologies to remove barriers and improve learning efficiency for large numbers of students in STEM curricula leading to a full-spectrum of health-related occupations.

描述（由申请人提供）：利用感知和适应性学习推进化学教育本提案涉及广泛的挑战领域12)科学、技术、工程和数学教育以及具体的挑战主题12- od -101：教育方法对提高STEM能力的有效性。这项工作将完善和测试化学学习模块的效果，这些模块结合了先进的感知学习和自适应学习技术，这两种技术都有很大的潜力，但在很大程度上尚未开发，可以改善STEM学习。目标学习群体将是参加基础化学课程的社区大学学生。这些学生是一个庞大而重要的群体，代表了广泛的健康和科学相关职业的相当大的人才库。该项目旨在解决限制学生学习的两个主要问题。一个是学生掌握和流畅处理关键结构和关系的能力。最近的研究表明，这个问题可以通过嵌入在学习技术中的感知学习原理获得巨大的成功。第二个问题是，学习不能适应学习者个人的需要。这些限制可以通过使用自适应学习技术来克服，在这种技术中，学习事件是基于学习者的准确性和速度进行排序的。要测试的学习干预采取感知学习模块（PLMs）的形式。通过简短的交互式试验，PLMs加速了学习者快速准确地处理复杂领域中的关键结构和关系的能力。plm是基于网络的；他们通过互联网上的标准浏览器提供学习和评估；而且它们可以很容易地扩大使用范围。该技术将结合最近获得专利的自适应学习算法，该算法使用连续的性能数据流来优化学习和记忆原理，从而提高学习和评估的效率。该项目团队由认知科学、学习技术、课程开发和评估、化学和化学教育方面的专家组成，将改进先前开发的两个化学plm，并使用现有的自适应学习软件开发一个新的plm，从而允许对这些技术进行广泛的测试。将在社区大学化学课程中进行实验室试点研究和全面的有效性研究。疗效研究将包括按受试者随机分组；治疗组将与对照组进行比较，对照组使用传统材料的时间相当；并将包括测试知觉/适应性学习的特定组成部分的有效性的条件。所提出的有效性研究预计将产生强大的学习收益，表明感知学习产生模式识别和流畅性的潜力，以及适应学习技术适应个人学习需求和产生精通的潜力。研究结果将对化学教育和其他STEM领域的学习产生影响，特别是对那些难以接受传统教学方法的学生。