基于大数据与指标融合的高校“学研用创”教学模式效果评价

摘要

信息技术与人工智能的快速发展使教学形式与教学方法日趋多样化。传统课堂教学评价多采用课堂提问、作业反馈、期末问卷等方式，普遍存在主观性强、滞后性明显、覆盖不全等不足，难以帮助教师及时把握课堂教学质量；而当前教学更强调将学、研、用、创四个环节结合起来进行评价，因此亟需一种新的教学质量评价方法。为提升某师范院校各专业“学研用创”教学模式的实施效果，本文采用问卷调查法与访谈法，从“学研用创”教学模式概况、教学态度、教学内容、教学能力和教学管理五个维度展开调查与评价。研究发现，各专业在实施该教学模式的过程中存在教学互动效果有待提升、教学内容丰富性与拓展性不足、小组讨论与实践课程开展不便、线上教学纪律不够严格、课程平台资源建设欠缺等问题。据此提出课前预习、课中拓展、课后巩固以提升教学互动效果，结合大数据技术积极整合教学资源、丰富教学内容，建立合理有效的小组激励与评价机制，结合各专业特点选择适宜的课程网络资源，以及加强教学管理、改善教学秩序等五条对策。最后，本文提出一种基于大数据与指标融合的高校“学研用创”教学模式效果评价方法，通过融合多种评价因素对教学效果进行分析，以实现对教学质量的实时客观评价。

Abstract

The rapid development of information technology and artificial intelligence has made teaching forms and teaching methods increasingly diversified. Traditional classroom teaching evaluation mostly relies on classroom questioning, homework feedback and end-of-term questionnaires, which are subjective, lagging and incomplete, and make it difficult for teachers to grasp the quality of classroom teaching in time. Current teaching places greater emphasis on evaluating the four linked stages of learning, researching, applying and creating, so a new method of evaluating teaching quality is urgently needed. In order to improve the effectiveness of the "learning, researching, applying and creating" teaching mode in the various majors of a normal college, this paper uses questionnaires and interviews to investigate and evaluate the mode along five dimensions: an overview of the mode, teaching attitude, teaching content, teaching ability and teaching management. The study finds that the mode suffers from insufficient teaching interaction, limited richness and extension of teaching content, inconvenient group discussion and practical sessions, lax online teaching discipline, and inadequate course platform resources. Five countermeasures are accordingly proposed: previewing before class, expanding during class and consolidating after class to improve the effect of teaching interaction; actively integrating teaching resources with big data technology to enrich teaching content; establishing a reasonable and effective group incentive and evaluation mechanism; selecting appropriate online course resources according to the characteristics of each major; and strengthening teaching management to improve teaching order. Finally, an effectiveness evaluation method for the "learning, researching, applying and creating" teaching mode in colleges and universities based on the integration of big data and indicators is proposed, which analyses teaching effectiveness by combining multiple evaluation factors so as to achieve real-time and objective evaluation of teaching quality.