When searching a knowledge repository such as Wikipedia or the Internet, the user doesn’t always know what they are looking for. Indeed, it is often the case that a user wishes to find information about a concept that was completely unknown to them prior to the search. In this paper we describe C-Link, which provides the user with a method for searching for unknown concepts which lie between two known concepts. C-Link does this by modeling the knowledge repository as a weighted, directed graph where nodes are concepts and arc weights give the degree of “relatedness” between concepts. An experimental study was undertaken with 59 participants to investigate the performance of C-Link compared to standard search approaches. Statistical analysis of the results shows great potential for C-Link as a search tool.

There is little doubt that the use of robots in introductory classes is an effective way to spark an initial interest in Computer Science and recruit students into our classes, and subsequently recruit some of them as Computer Science majors. But when the semester is over, the vast majority of our students are unlikely to see robots in the classroom again until they take advanced courses in AI or Robotics. It is time for those of us who are proponents of the use of robots in Introductory Computer Science to start thinking seriously about how we are using robots in our classes, and how to sustain the interest and enthusiasm of our students as they move on to more traditional courses. While the focus of this paper is on the use of robots in Introductory Computer Science courses, my goal is to initiate a more general discussion on the use of any sort of cool new technology (tangible or not) into both undergraduate and K-12 education. These technologies successfully attract students to study subjects that we ourselves are deeply engaged in. But we need to discuss as a community what happens when our individual classes conclude and the rest of their studies commence.

This paper reports on the Design Compass, a classroom tool for helping students record and reflect on their design process as they work on and complete a design challenge. The Design Compass software provides an interface where students can identify and record the various design steps they used while performing them, and add digital notes and pictures to document their work. In the Design Log view, students can review steps taken, and print the record of work done, which can be shared and discussed with their instructor or classmates. The paper describes the concepts underlying the creation of the Design Compass, its features as a metacognitive tool and how it works, and provides scenarios of its use as a teaching and assessment tool with eighth-grade technology education students, and in teacher professional development workshops.

This paper introduces the IRIS mobile robot project. IRIS is a largely student designed and implemented mobile robot platform created to provide a mechanism for classroom explorations of topics in artificial intelligence, cognitive science, and robotics. It has been designed to be used by students from middle school through college.

Evaluating new educational programs and tools, especially those targeted at difficult-to-assess learning goals can be quite challenging due to the small number of participants typically engaged with pilot programs. The focus of the evaluation, then, should be on collecting rich data from each participant about their experience in the workshop and their progress towards meeting the workshop’s learning goals. We present a novel evaluation technique, the debugging task, that seeks to assess at post-workshop a participant’s independent ability to use the tools, skills, and materials of the workshop. The technique is presented in the context of Robot Diaries, a program to develop a robotics design activity centered on crafts materials and expressiveness, and targeted to middle school girls. The paper discusses the rationale for the debugging task, its implementation, and the results and analyses of girls completing the task.

We present the design and deployment of a physical computing platform developed for a crossdisciplinary introduction to biology and computer science. Using the accessible Arduino interface as its foundation, students instantiate increasingly nuanced physical interactions with the environment. Biological and computational ideas receive equal attention through three layered projects that span from circuit design through the co-evolution of predator-prey robot behaviors. The low-overhead platform presented here scales to support sophisticated projects at surprisingly modest time-and-money costs

For the past several years, we have been using robots in our introductory computer science course. Although this has been challenging for many reasons, it has also been very rewarding on a number of fronts, both for the students and for us. However, in order for this to occur, we had to adapt to what we perceived as “chaotic code.” In this paper we describe lessons learned by watching what the students do, where they have trouble, and what they enjoy. Further, we discuss what the implications of focusing on creativity has had on teaching and assessment.

But whereas in the general Rwandan populace males tend Despite the increasing ubiquity of mobile phones in the developing to be much better educated (76.3% of males are literate, but world, remarkably little is known about the structure only 64.7% of females), among mobile phone users it is the and demographics of the mobile phone market. While a women who achieve higher levels of education: the median few qualitative studies have detailed social norms of phone woman completes secondary school, while the median man use in specific communities (Donner 2007; Burrell 2009), does not (t 4.79). Table 1 shows a few statistics on asset and a handful of quantitative researchers have begun to analyze ownership, with associated sampling error.

A key challenge for policymakers in many developing countries is to decide which intervention or collection of interventions works best to improve learning outcomes in their schools. Our aim is to develop a causal model that explains student learning outcomes in terms of observable characteristics as well as conditions and processes difficult to observe directly. We start with a theoretical model based on the results of previous research, direct experience and experts’ knowledge in the field. This model is then refined through application of supervised learning methods to available data sets. Once calibrated with local data in a country, the model estimates the probability that a given intervention would affect learning outcomes.

Cellular phones can be used as mobile sensors, continuously logging users’ behavior including movement, communication and proximity to others. While it is well understood that data generated from mobile phones includes a record of phone calls, there are also more sophisticated data types, such as Bluetooth or cell tower proximity logging, which reveal movement patterns and day-to-day human interactions. We explore the possibility of using mobile phone data to compare movement and communication patterns across cultures. The goal of this proof-of-concept study is to quantify behavior in order to compare different populations. We compare our ability to predict future calling behavior and movement patterns from the cellular phone data of subjects in two distinct groups: a set of university students at MIT in the United States and the University of Nairobi in Kenya. In addition, we show how Bluetooth data may be used to estimate the diffusion of an airborne pathogen outbreak in the different populations.