Ray Bareiss’s research while affiliated with Carnegie Mellon University and other places

This paper describes the design and initial evaluation of a mobile application for training Community Emergency Response Teams. Our goal is to model the kind of remediation and performance support provided in high-end eLearning systems, and provide it during hands-on learning in the real world, using mobile phones and sensors embedded in the environment. Thus far we have designed the learning system and tested it with real users, simulating sensor-based activity recognition using an Android-based Wizard of Oz system that we have developed. Our initial user tests found that users were able to use the system to complete tasks, including some that they had never done before. They had little difficulty understanding the interaction mechanism, and overall reacted positively to the system. Though learner reaction was generally positive, these user tests yielded important feedback about ways we can better manage the division between the real world and the digital world. © 2013 ICST Institute for Computer Science, Social Informatics and Telecommunications Engineering.

Although mobile-based prototyping platforms are numerous, there are currently no tools that support Wizard of Oz interactions on Android. This paper describes a Wizard of Oz prototyping system for Android, via which a designer can enhance digitally generated mock-ups or scanned-in paper sketches with interactive widgets and automated screen transitions. Screen transitions can be based on user action such as a button presses, triggered manually by an experimenter observing from a laptop or triggered based on the user's location or the time. We have integrated scenario-based user testing, a context in which Wizard of Oz testing is often used, by providing support for location- and time-based display of videos and screens in the prototype. It is our hope that this system will find wider use in the design community.

This paper presents the initial results of a study of the evolution of students’ knowledge of software engineering from the beginning to the end of a master’s degree curriculum in software engineering. Students were presented with a problem involving the initiation of a complex new project at the beginning of the program and again at the end of the program’s formal coursework. After considering the problem each time, students were asked what questions they had as the senior software engineer, which software engineering processes need to be put into place, and to enumerate any other issues they saw. Statistical analysis indicates that their enumeration of software processes in the post condition is very significantly richer than in the pre condition. They also gave significantly more responses about requirements, design, and engineering management in the post condition. Qualitative analysis suggests that the students’ questions in these areas were also more sophisticated in the post condition, suggesting, in accordance with the theory of “transfer as preparation for future learning,” that they are moving along a trajectory towards expertise.

We believe the master's program in Software Engineering offered by Carnegie Mellon University's Silicon Valley Campus to be unique in that it is entirely team-based and project-centered [1]. Students learn by doing as they are coached just in time by faculty in the context of authentic projects, and they are evaluated on the work they produce. Student satisfaction is high: 94% believe that the program has given them a competitive advantage with respect to their professional peers, and their promotion and salary histories bear out this belief. This tutorial introduces the attendees to our learn-by-doing instructional approach through participation in a learn by doing experience, performing a usability analysis of a commercial website, followed by discussion to highlight what we believe to be important principles of teaching by coaching.

This research addresses the use of mobile devices with both embedded and external sensors to provide contextualized help, advice, and remediation to learners engaged in real-world learn-by-doing tasks. This work is situated within the context of learning a complex procedure, in particular emergency responders learning to conduct urban search and rescue operations. Research issues include the design and delivery of contextualized performance support and the inferring of learner actions and intentions from sensor data to ensure that the right support is delivered just in time, as it is relevant to what the learner is doing.

As emergency first responders and commanders increasingly use mobile phones, tablets, and social media to communicate, coordinate, and manage information during disasters, we see a need and opportunity to provide a mobile device-appropriate semantic layer to a geographically-based common operating picture. The challenge is to provide a simple, usable structure for a rapidly growing body of information to simplify the development of situational awareness in an unfolding disaster. We use a hyperlinked structure based on the ASK model to organize information in a readily accessible form. In this paper we describe our initial design and experience with an Android-based prototype, supported by a Ruby on Rails-based repository service. Our prototype allows the incorporation, aggregation, assessment, and redistribution of dynamic human-generated and sensor-derived information.

Students at Carnegie Mellon Silicon Valley complete a team-based practicum project for an industrial sponsor as the capstone of their master’s education in software engineering. Over time, the faculty member who typically serves as advisor for such projects has been disturbed by the failure of several student teams to transfer some relevant knowledge and skills from the formal curriculum to the relatively unstructured practicum project environment. We conducted a survey of all 2010 software engineering students to ascertain the most significant selfreported shortcomings. This paper presents the survey data and then discusses the results in terms of a theory of transfer; as part of this discussion recent and possible future changes to instruction are identified. Carnegie Mellon Silicon Valley provides a unique master’s program in software engineering targeting both working professionals, who complete the program part time over two years, and recent graduates, who complete it full time in one year. The program aligns with the emerging Silicon Valley approach to software engineering which is agile, product focused, entrepreneurial, and tends to focus on smaller projects completed on short timelines. The program features a unique team-based and project-centered pedagogy in which students learn by doing . They work on realistic projects, are coached by faculty to learn just in time, and are evaluated based on the work they produce. The program is bracketed by end-to-end software development experiences. The beginning Foundations of Software Engineering course (described in a later section of this paper) involves completing a faculty-provided project which is realistic but designed with pedagogical intent; its completion requires particular knowledge and skills. The final Practicum Project is a realworld development project undertaken for a client; it provides a capstone experience in which students are expected to transfer the knowledge and skills learned over the course of the program to this authentic final project.

At Carnegie Mellon's Silicon Valley campus we employ a learn-by-doing educational approach in which nearly all student learning, and thus instruction, is in the context of realistic, team-based projects. Consequently, we have adopted coaching as our predominant teaching model. In this paper we reflect on our experience with the nature of teaching by coaching using a framework derived from Cognitive Apprenticeship, and explain how we employ the techniques it suggests in our teaching. We also discuss a range of instructional tensions that arise in teaching by coaching and present a survey of student attitudes regarding the effectiveness of our approach.

Given the unique nature of the software business, the faculty of Carnegie Mellon University's Silicon Valley campus concluded that mid-career software professionals would be better served by a tailored master's degree focusing on software management and more broadly on the business of software than by a typical MBA. Our software management master's program integrates business, technical, and soft skills to prepare our students for technical leadership in their current companies or in entrepreneurial ventures. Our initial program built on the strengths of Carnegie Mellon's world-class software engineering education. We targeted students working in large companies, engaged in large-scale enterprise software projects, employing ¿high ceremony¿ software development processes. However, the majority of our students came from Silicon Valley companies which shared a product development focus, engaged in smaller projects, favored agile development processes, and measured development cycles in weeks rather than years. Our program has evolved to align with these interests. It employs a unique team-based and project-based pedagogy which emphasizes practical skills over theory, depth over breadth, and coaching over lecturing. High student satisfaction and growing enrollment have validated our curriculum decisions and have led us to make this program the educational centerpiece of Carnegie Mellon's Silicon Valley campus.