Student conversations during computing: How are students collaborating while computing?
October 27, 2016
Within the LTEC project, we are developing learning trajectories for integrated mathematics and computing. In addition to examining the literature and existing curricula for both implicit and explicit goals and learning progressions, we also examine implementation of integrated mathematics and computing in existing elementary classrooms. As part of this work, we conduct classroom observations and interviews with teachers, and make video screen recordings of students as they complete computing tasks. We use these multiple data sources in order to gain a more robust understanding of how these integrated lessons are developed and taught by the teachers as well as how students are engaging in the process of computing.
Figure 1: Example of C-COI interface
A fun aspect of this data analysis involves watching videos of students’ computer screens as they attempt to solve computational problems and listening to their conversations within the integrated mathematics and computing lessons. We use software called Screencastify, a simple video screen recorder for the Google Chrome web browser. This software allows us to hear the conversations that students have and see video of the students’ computer screens as they work on computer programming activities related to their mathematics instruction.
We use the Collaborative Computing Observation Instrument (the C-COI; Israel et al., in press), to analyze the recordings of the on-screen individual and collaborative behaviors of students as they engage in computing activities. This instrument allows us to code what the students are doing, whether they are struggling with the task, whether their difficulty is related to the mathematics or the computing, and how they interact with peers and teachers. It also allows for us to input extensive field notes such as transcriptions of conversations and descriptions of the computing and mathematics tasks.
We began by observing nine purposefully selected students to learn about the types of collaborative interactions they had during computing activities. Each student was observed at least three times in order to gain a more complete picture of their computational interactions. Overall, we analyzed 29 separate videos with each video approximately 25 minutes in length. This data analysis revealed three main types of interactions.
- Collaborative problem solving
- Expressing curiosity, excitement, and accomplishment
- Off-task socialization
Collaborative problem solving: This type of discourse accounted for about 50% of student-student and teacher-student interactions. These interactions typically occurred when students needed help with solving a problem they faced during the computing task. For example, when some students programmed simulations of fraction word problems, they did not have a strong command of conditionals such as if_______, then ______, else ________. They often tried working through their code independently and then asked a peer or the teacher to help them. Other students struggled with the mathematics and asked for help with creating fraction word problems.
Figure 2: An example of a fraction word problem
Excitement, Curiosity, and Accomplishment: A little less than one-fifth of all interactions that we analyzed fell into the category of the student expressing excitement, curiosity or accomplishment. Often students’ conversations in the integrated mathematics and CS/CT lessons related to either expressing excitement and accomplishment about something that they correctly programmed or curiosity about the work of a friend. For example, if a student finally debugged their program, they often expressed their excitement or if their peer created an animation that they were unfamiliar with, they would say something such as, “Cool, how did you do that?”
Off-task socialization: Approximately one-third of all conversations were related to off task behaviors and simply reflected social interactions between peers and their teachers. Typical conversations were about what the students would do after school, about games and shows that they have watched, or other banter between peers.
Next Steps
In the next phase of our data collection and analysis, which will take place this spring, we will begin to test emerging learning progressions within lessons that integrate mathematics and CS/CT. Questions that we are asking include: to what extent are the mathematics and CS/CT integrated? how are students performing within the lessons? and what challenges and barriers the do teachers report? We will also look at the collaborative problem solving conversations using the C-COI to better understand the relationship between challenges that the students face with mathematical understanding (e.g., conceptual understand of fractions) and challenges the students face related to computing (e.g., understanding how to use conditional statements or how to debug a program in a systematic way). Our hope is to develop learning progressions that are flexible enough to account for the academic diversity typically found in elementary classrooms. For example, students may still have misconceptions about fractions, so the computing tasks integrated into the math lessons can help build stronger understanding of fractions.
Bearing witness to student conversations has always been a pronounced benefit of classroom observations. We are thrilled about the added value afforded by the screen-recording technology and our C-COI analysis. We expect such insight into student conversations during computing to specifically enhance our project’s research. In the coming months, we will share more about C-COI and how analysis of student conversations may shape our work.