Using Twitter as a diagnostic teaching and learning assessment tool

Higher education students coming from different regions and schools have different interests and knowledge levels. These differences can be exploited by teachers to improve the course efficiency. Knowing beforehand the misconceptions and the prior knowledge of the students, the teacher can tune the content of the lecture accordingly. In traditional systems, short essay, multiple choice or true-false diagnostic quizzes that include several potential misconceptions related to the targeted learning, are often practiced for this purpose. This approach reveals the differences in prior knowledge, misconceptions and deficiencies in prerequisite skills amongst the students. The teacher armed with this information can organize both the content and the structure of his/her teaching more efficiently. In this paper, we propose using Twitter as a diagnostic teaching and learning assessment tool. In this scenario the teacher tweets hashtags related to key concepts or misconceptions. The comments of the students are retrieved using Twitter APIs and stored in a local database. The teacher views and analyzes the retrieved data to tune her/his instruction. After lecturing, the same hashtags are sent and responses are collected. Analysis of the data before and after will reveal how much learning is achieved. Besides, this tool will enable instructors to provide some hints to students about the topic of the lecture and engage students more through the use of social media.