Introductory programming meets the real world

Abstract

Too many students in introductory programming classes fail to understand the significance and utility of the concepts being taught. Their low motivation impacts their learning. One contributing factor is pedagogy that emphasizes computing for its own sake and assignments that are abstract, such as computing the factorial function.Many educators have improved on such traditional approaches by teaching concepts in contexts that students find more relevant, such as games, robots, and media. Now, it is time to take the next step.In this special session, participants will develop and discuss ways to teach introductory programming by means of real-world data analysis problems from science, engineering, business, and the humanities. Students can be motivated to learn programming in order to analyze DNA, predict the outcome of elections, detect fraudulent data, suggest friends in a social network, determine the authorship of texts, and more (see Section 3.4 for more examples). The approach is more than just a collection of "nifty assignments": rather, it affects the choice of topics and pedagogy, all of which together lead to greater student satisfaction.The approach has been successfully used at 4 colleges and universities. The classes were effective for both CS and non-CS majors. Neither the computing material nor the problems need to be "dumbed down". At the end of the term students were amazed and delighted at the real data analysis that they could perform. They were excited about applying computation in their work and about learning more.The special session contains a mix of activities, including comparative analysis of introductory classes; group discussion of curriculum design; a mini-panel discussing how the approach has worked in practice; and brainstorming about example assignments and curriculum revision.

Position paper: From interest to usefulness with BlockPy, a block-based, educational environment

“…and Scratch support game design. Data Science for Introductory Computing is a growing movement, with many instructors recognizing the inherent value [1], [2] Data science provides an authentic, useful context for every kind of student, since exploring data-oriented problems is something that almost all fields are beginning to find relevant [3], [4]. Additionally, it is readily possible to find data sources that connect to the world around the student and their past experiences, establishing a sense of personalized interest.…”

Most common fixes students use to improve the correctness of their programs

“…Despite the importance of programming, there are many difficulties students face when they have to learn how to program. In general, the problems range from a lack of understanding of basic programming concepts [1], [6], [2] to the lack of motivation to perform programming activities [3], [4].…”

Design and Preliminary Results From a Computational Thinking Course

“…However, we believe that big data is seen by students as "useful" which is more engaging than media computation which is seen as "interesting" [16]. Our course shares with [17] the sense of engaging students with real world data. What we offer is that the data and questions to be answered are decided by the student and are not predetermined assignments.…”