Ubiquitous computing has led to inevitable interactions with computing technologies in individuals' everyday lives in the modern era of computing.These technology interactions are becoming increasingly invisible and intrusive in daily life.To navigate this computational landscape with agency, individuals take charge of their interactions in various ways.This form of engagement is inherently democratic, enabling individuals to cultivate a first-person, autonomous experience of computational technologies, free from apprehension or uncertainty.However, the characteristics of ubiquitous computing interactions can overwhelm children in urban Indian contexts who have limited exposure to technology interaction contexts.The authors of this Work-in-Progress (WiP) present AuthentiCT, a playground that emulates everyday computational interactions designed for urban Indian students in grades 7-8 (ages 11-14).AuthentiCT provides a structured space where students engage in everyday activities using computational objects, ultimately leading to the creation of a design project through three phases-Explore, Solve, and Evolve.This WiP submission outlines the research study plan.The authors anticipate that the study will offer insights into how learners from this context navigate everyday interactions through different dimensions of empowerment to take charge in AuthentiCT environment, along with the challenges they encounter.

Image description creation is utilised in a variety of applications, such as automatic script development, medical image annotation, and news reporting. However, the detailed description of the image with the relevant region is complicated using deep learning approaches. In this paper, an intelligent Red-tailed Hawk Generative Deep Learning Model is presented for generating image descriptions. The suggested technique reduces the loss function of the network model while also updating the weight parameter using the meta-heuristic Red-tailed Hawk Optimizer (RTHO). Extensive simulation experiments are carried out to assess the suggested model. The obtained results demonstrate that utilising the proposed approach improves the BiLingual Evaluation Understudy (BLEU)-1, BLEU-2, and METEOR scores to 0.74, 0.44, and 0.53, respectively.

Educational Robotics (ER) is a Held of study that involves the integration of robotics into educational settings to enhance the learning experience. The primary goal is to engage students in hands-on, interactive activities that promote problem-solving, creativity, collaboration, and critical thinking. This study delves into the effectiveness of scaffolds to foster problem-solving through robotics activities, focusing on undergraduate engineering students. Through detailed analysis of participant activities, artifacts, and semi-structured interviews, the research addresses questions regarding scaffold effectiveness and student perceptions of a robotics learning platform. Key findings reveal challenges related to limited prior knowledge, team dynamics, and motivation. The study highlights the importance of clear instructions, well-defined guidelines, and motivation-related resources to enhance engagement and problem-solving skills.

Education policy implementation is a highly complex process involving multiple stakeholders, including policymakers, administrators, teachers, students, parents, and community members. The interactions and ongoing decision-making process by the different stakeholders can immensely affect the policy outcomes. The process being highly contextual, varying with culture, politics, and socio- economic conditions, it is crucial to study the role of different factors/determinants influencing the design and implementation of policies in different settings. The present study is a preliminary attempt to categorize and analyze some of the perceived realities of different stakeholders involved in the implementation of an education policy. Two determinant types extensively used in implementation research were used to analyze the data. When passed through multiple levels, the policy guidelines get shaped and reshaped by the local agenda and respective modus operandi of each stakeholder involved in the implementation process. The results emphasize the need to develop strategies to better understand the role of different contextual factors — how and why they influence the implementation of education policies involving technology.

Habits are formed when people perform repeated actions in a certain context while pursuing a goal. In the context of a semester-long Instructional System Design course, we show how the goal of designing a real-life website for the sensitization of teachers and peers toward disabled students led to the construction of certain desirable learning habits. The participants in the course were the default IS designers and the Persons with Disability (PwD) cell of the institute was the client. Anchored in the Interest-driven creator (IDC) theory, this study provides evidence for the three conceptual components of the habit loop- cuing environment, routine, and harmony. We argue that the real-life goal provided a fertile ground for routinizing the behavioral and conceptual activities of the participants. We use a combination of deductive and inductive coding to analyze the data sources of interviews, class interaction observations, shared documents for class reflection, and class interaction records in a virtual space. Our findings suggest that the physical and virtual spaces for regular class interaction, learners' routine interaction with the group members, and the constant sharing-cum-discussion of ideas scaffolded desirable learning habits as they pursued the common goal of website design. This study has implications for fostering desirable learning habits in regular classroom interactions.

In semester-long courses, the trajectory of students' interest hits multiple highs and lows as the course progresses. In general, sustaining students' interest is a challenge, which becomes even more important when there is a real-world project with an expected deliverable. This study emphasizes investigating how instructors’ strategies help in sustaining students’ interest in instructional system design (ISD) course. The course participants developed a real-world project involving training resources for sensitization about the needs and challenges of persons with disabilities (PwD) in an educational institute. We have analyzed interview data of fifteen students and one instructor, survey data of the same students, and In-class observations by researchers. We have identified instructors’ strategies which were implemented thoughtfully and supported by interest-driven creator (IDC) theory. We have mapped indicators from student responses to the components of the interest cycle i.e. triggering, immersing, and extending. The findings of the study show that course strategies supported by IDC theory played an important role in sustaining the students’ interest throughout the ISD course while ensuring both conceptual learning and project execution.

Self-directed learning presents a promising approach to enable students to achieve self-reliance and cultivate greater ownership over their learning pursuits. In the current teaching-learning scenarios, the implementation of classroom-oriented self-directed learning (SDL) strategies does not achieve their desired goal. The primary reason may be that the teachers are not trained to implement these strategies. According to the literature, learners face difficulties in following different SDL strategies. Question posing (QP) serves as a tool that can help learners understand the concept, clear misconceptions, and collaborate with peers to construct their knowledge. We have analyzed existing papers on question-posing-based classroom- oriented self-directed learning strategies to find how question-posing may help students overcome their difficulties and find ownership in their learning. We find that QP-based teaching-learning approaches require well-designed activities that can help students elicit questions and with which students can navigate in achieving ownership of their learning. The paper concludes with the identification of a QP-based strategy that conforms to the essential set of requirements of self-directed learning.

In the rapidly changing ChatGPT world, human skills training is the need of the hour. With a large amount of data, ChatGPT is training itself day by day to understand human prompts and to provide appropriate results. A lot of prompt engineering courses educate learners in structuring the prompts based on how the ChatGPT engine processes any prompt and response. However, these courses do not target specific cognitive skills required by users (learners) to unfold, understand, and express what they really need and want to know from ChatGPT. In this paper, we look at ChatGPT as a tool to support knowledge acquisition and we discuss the questioning skill as an essential cognitive skill required to interact with and make optimal use of ChatGPT capabilities. We argue that risk to the fairness of access does not just stem from the monetary availability of such technologies, but it can also arise from the unpreparedness of the target users. The AI and ethics of AI literacy communities should also focus on training individuals on the cognitive skills needed to become optimal users of such technologies.

The integration of ubiquitous technologies with classroom interactions has the potential to foster positive learning habits in students. The instructors at Educational Technology Program in IIT Bombay tackled the challenge of remote learning during the COVID-19 lockdown by conceptualizing the use of the Slack platform to promote learning habits among their graduate students. Grounded in the IDC theory specifically developed for the Asian population, the design of this pedagogical intervention aimed to promote students’ habit of conveying complex ideas in an accessible manner through two learning activities aligned with their interests. Conversation analysis was used to examine instructors' actions to develop learning habits in students, and member check interviews were conducted with instructors to verify the pedagogical approach and findings. The study demonstrated how the instructors' pedagogical intervention on the Slack platform supported the development of learning habits among graduate students. The results exhibited the mapping of individual components of the habit loop, i.e., cuing, routine and harmony with the design and outcome of the approach. Students’ satisfaction with routine activities and impatience for creations from the learning activities indicated harmony which eventually leads to habit formation. The continual pursuit of learning activities without instructor involvement also suggested habit activation. The present study contributes to the current understanding of effective pedagogical practices to foster good learning habits by leveraging ubiquitous learning tools.

Disciplinary practices are processes and skills applied for sensemaking, reasoning and problem solving. Studies have shown that experts are able to spontaneously apply these skills but novices have difficulty due to various reasons. The aim of this paper is to showcase learning environments that foster disciplinary practices in undergraduate computing students in three contexts - data structures, software design and computer networks. Findings from our studies show that students are able to apply these disciplinary practices to solve ill-structured problems. These findings provide motivation for exploring disciplinary practices in other CS courses as well.

An important skill graduating computing students require is to evaluate a given software design and ensure that it satisfies the intended requirements. Prior work has shown that while working with software designs, experts think deeply about the design and simulate scenarios where the design does not satisfy the requirements. In this paper, we examine how students evaluate a given set of software design diagrams (UML class and sequence diagrams) against the given requirements.

Integration of Information and Communication Technology (ICT) in teaching and learning in schools has been hindered by many barriers, including lack of in-service teacher training, teacher beliefs and lack of infrastructure. In the effort to solve the challenge of teacher training in Tanzani, few in-service teachers, based on different parameters, are selected to participate in the face to face ICT training at the specified training centre. Scaling of such teacher training initiatives has been challenging over time. To reach more school teachers, we developed a ten-day online cours, run over Moodle. A total of 134 teachers from all the regions of Tanzania registered and participated. Topics were developed based on the preference of the in-service teachers. Online surveys were used to collect qualitative and quantitative data before and after the course. Teachers were active during the duration of the course and many of them applied the skills in their schools by improving their teaching strategies, use of technology tools and sharing experiences with other teachers in their schools.

As MOOCs are expanding in popularity and scope, problems such as lack of learner engagement and low participation in discussion forums have been reported. Challenges in MOOCs not only include large numbers of learners but great diversity in learners' background, ages, experiences, and motivation for participating. While issues such as certification, equitable access, and sustainability are being discussed, without advances in the pedagogical format, MOOCs may end up being an online version of a traditional lecture format. Instructors, especially those who are new to the online learning format need support in designing MOOCs to promote learner engagement, address learner diversity and cultivate peer learning. The Learner-centric MOOC (LCM) model guides instructors in maintaining a learner-centric pedagogical approach while planning, designing and orchestrating a MOOC. The model provides a set of guidelines, activity formats and actions that instructors can apply during various stages of the MOOC instructional design process. In this tutorial, we describe the structural and dynamic aspects of the LCM model, demonstrate the application of the model in various MOOCs and illustrate research results from MOOCs based on the LCM model. We will share activity constructors and templates that have been developed to scaffold instructors in applying the LCM model to design their MOOC.

Solving engineering design problems requires the students to explore and understand the solution space to think creatively. Most of the current teaching practices of problem-solving in the context of engineering design are very structured not allowing much room for exploration. "Making" is the act of building or adaptation of objects to understand the functions of our environment. It involves opportunities to order the immediate environment around oneself which can serve as a cognitive function to provide insight into multiple solution strategies. In this doctoral research, we propose to build a learning environment (LE) to support the learners in learning the key skills and processes essential for making. With the help of some maker-studies, we will try to identify the key skills and strategies that they apply while making. In studies with novice makers, we will try to determine the challenges faced in learning and application of such skills. The findings from these studies will guide the design of our LE to support the learning of making.

Novice researchers have difficulties in operationalization (breaking down of abstract concepts to measurables) and generalization (generalize the findings to make claims). We have designed a system called OPeD (Operationalizing using ProblEm Decomposition), for teaching learning of operationalization. OPeD trains novice researchers in operationalization through problem decomposition. OPeD is based on pedagogical theories of guided inquiry, problem visualization and adaptation. In order to visualize the operationalization process, OPeD guides the learner to create a decomposition tree and construct meaningful hypotheses based on the tree. The gradual and iterative construction of this tree can help learners develop their operationalization skills. In this paper we present the design of OPeD and provide an exemplar of a learner path in the context of educational research.

Divergent and convergent (D&C) thinking skills are important in solving software design problems. Divergent thinking involves processes like understanding the problem from multiple perspectives and generating multiple solutions to a problem. While, convergent thinking is evaluating and selecting the solution based on the criteria and constraints. These skills are important in software design process for better design outcomes. Studies have shown that students lack the abilities to apply these skills spontaneously to solve design problem. In this paper, we present the design of a Technology Enhanced Learning (TEL) environment with metacognitive support to foster D&C thinking skills in engineering students. The scaffolds are characterized in the form of prompts, examples, simulations, and D & C thinking tools to trigger D & C thinking during real life design problem solving in data structures. A study was conducted with second year computer engineering students to find the effectiveness of the metacognitive and cognitive prompts in doing the D & C thinking activities. The results show that design features have helped students perform the activities effectively. These results are supported with student's perception survey and student interviews.

Computer Networks, an undergraduate computer science course, is taught through a variety of new technological tools but more attention on assessment strategies using those technological tools is desirable. Research studies have shown that assessment methods also influence students' learning. Current assessment techniques, even those which include technology, focus more on summative assessment rather than formative. Formative assessment is necessary for teaching and assessment of complex skills like troubleshooting or network design. Therefore, there exists a need for assessments to capture students' problem solving process and chosen approaches during the assessment. By tracking a student's behaviors in an immersive assessment environment, the path that the student takes towards the solution can be studied. Virtual Worlds are naturally immersive environments and can be effectively used to record interactions that students made in the worlds. We have developed NetWorld in Open Wonderland, an open source software for creating 3D virtual worlds. NetWorld is a 3D virtual world built for detailed assessment of computer network concepts for computer science undergraduate students. This detailed assessment happens at 3 levels -- conceptual understanding, diagnostic abilities and the ability to design a network. This paper describes the design principles and implementation of NetWorld and a plan to evaluate its usability.

In this paper, we present a software tool to measure alignment of Assessment instrument (AI) with a set of learning objectives (LOs) of a course. Alignment of syllabus, LO and AI is a major parameter determining the quality of an AI. The tool helps to considerably reduce the time and effort needed by teachers to ensure this alignment. It takes syllabus, a set of LOs and domain ontology as input. An ontology based knowledge representation mechanism is designed to integrate the contents of syllabus, LOs and AI. Alignment is measured in terms of both concepts covered and cognitive level used. The Data Structures course of second year engineering curriculum is chosen as the domain. The accuracy of this tool is tested by comparing the system generated alignment measure with the expert teachers and a confusion matrix is generated. We got an average accuracy of 90% for concepts alignment and 95% agreement in cognitive level alignment.

Most major Massive Open Online Course (MOOC) providers are focusing on design of xMOOCs. In these courses, a central course design team develops necessary learning content (in form of videos and/or documents), automated assessments and manages discussion forums to engage the participants in a structured manner. However the xMOOCs have been criticized for their cognitive-behaviourist pedagogic design, lower student engagement with discussion forums and lower completion rates that make it unsuitable for direct use in Teacher Professional Development (TPD). In this paper we introduce the idea of ‘Learner Perseverance’ that can be used as a better design goal for an xMOOC developed for TPD. The design principles of Immersivity and Pertinency were utilized in adapting the xMOOC components of videos, auto-graded assessment problems and discussion forums for a TPD MOOC (ET601Tx) to achieve learner perseverance. It was seen that there were 3447 active participants (67.5% of enrolled) in the course, i.e. people who have accessed courseware at least once. The data from the course logs show that 1201 (47.1%) active learners had participated in the discussion forum generating 5023 discussion threads generating 9861 comments (i.e. 4 threads and 8 comments per active learner who participated in the discussion forum). It was also seen that there is a completion rate of 36.58% (1261 learners) for ET601Tx, which is quite high compared to the average completion rates reported in xMOOCs (6-7%). The course completion survey indicated that these pedagogical designs were useful and relevant for the teachers in their own practice. Based on these findings we recommend use of a ‘Learner Perseverance’ based design for improving learner participation in xMOOCs that are used for TPD.

The design of an assessment instrument (AI) is one of the major components of assessment process. The teachers have to generate AI aligned with the course learning objectives (LOs) within the boundary of topics defined by the syllabus of that course. When the instrument covers the LO fairly, it covers the subject matter defined by the syllabus fairly. This paper discusses an approach towards integrating both the contents and cognitive level defined in the LOs into the domain ontology for a Data structures course. This forms the first step towards building an automated system to measure the alignment of AI to course LOs. In the proposed approach, the notion of domain ontology is introduced on which the LOs are overlaid. Concepts and cognitive levels from LOs are extracted using Natural Language Processing. Mapping these to the nodes of the ontology also involves complex processes to take decisions about selection of nodes and traversal of links. For each of these, issues and challenges are discussed in detail and a solution is proposed. We have done a prototype implementation of the system to test our design. The effectiveness of this framework was tested by comparing the manually generated results by the experienced teachers to the system generated results and obtained an average accuracy of 90%. The examples are taken from Data Structures course of second year engineering curriculum.

Spatial ability training is useful in developing problem solving skills in engineering drawing (ED). Mental rotation (MR) is a substantial part of spatial abilities. In a previous work we described a three-hour computer based 3D MR training module and showed that it improves MR skills of first year engineering undergraduates. In this paper, we present a study on the effectiveness of a two-week computer based 3D MR training on students' problem solving skills in ED. We performed a two-group experimental study and found that students who learned via computer based 3D MR training performed significantly better on ED posttests than students who learned the same concepts via traditional instruction. Responses of experimental group students on an open ended question revealed that they found the 3D MR training to be useful in resolving their ED problem solving difficulties.

Question posing by students is a valuable mechanism for learning. In this paper we demonstrate how student generated questions can result in unfolding of knowledge. We conducted field studies in Data Structures courses, where we provided a semi-structured question-posing situation to students. We analyzed the questions generated by students using inductive qualitative data analysis. We found that students pose exploratory questions and unfold knowledge using seven strategies, viz., Apply, Organize, Probe, Compare, Connect, Vary, and Implement. These strategies were validated within the data structures domain and were also found to be valid in another CS application domain (Artificial Intelligence). The content analysis of the questions has shown that students tend to unfold more conceptual knowledge than procedural knowledge.

Students, who study in their native language in K-12 and go on to do their undergraduate education in English, have difficulty in acquiring programming knowledge. Solutions targeted towards improving their English proficiency take time, while those that continue with native language in the classroom limit the students' ability to compete in a global market. Another solution could be the use of video-based instructional material to empower a student for self-paced learning. In this paper, we present a comparative study of classroom instruction versus self-paced screencasts for native language learners' acquisition of programming concepts. We conducted four introductory programming workshops, each of six days duration. Two workshops were classroom based, one having Hindi (native language) as the medium of instruction and other in English. Two other workshops were screencast based, again one in Hindi and one in English. We measured differences between the groups using a post-test, across different content types such as fact, concepts and process. We found that when medium of instruction is different from language of K-12 instruction, there is an adverse impact on learning. However, when self-paced screencast is used instead of classroom environment, there is a statistically significant improvement in performance. Our work informs the choice of MoI and choice of environment for native language learners.

First year undergraduate students in engineering often face difficulties in solving engineering drawing (ED) problems. The potential reasons for this could be either the students' deficiency in visualizing spatial relationships or the instructional method used. We have developed a three-hour MR training using Blender 3D, an open source 3D animation software. In this paper, we present experimental evidence of the effect of our training on the improvement of problem solving skills in ED. We analyzed the results and found them to be significant. Also, the qualitative analysis of students' responses to the open ended questions revealed that, they found training useful in resolving their difficulties in solving ED problems.

We have created a visual representation called Stratified Attribute Tracking (SAT) Diagram to explicate trends that are otherwise implicit in learning analytics data. SAT Diagram is a unified graph that enables tracking individual attribute values in a dataset and stratifying them according to criteria set by the researcher. SAT diagram represents the transition of samples between strata across attributes. In this paper we introduce the SAT diagram and illustrate how to generate, interpret and analyze them. We believe the process of SAT diagram generation would enable exploring deeper research questions on learning data.

The outcome-based approach of education requires engineering faculty to be able to align the student learning objectives with their instructional and assessment strategies. With the increasing use of educational technology, faculty technology integration also becomes an essential part of this alignment. Though there exists instances of training programmes that help faculty to achieve this alignment and integration, there are no validated frameworks or models that will enable teacher educators to prepare good instructional development programmes for the faculty. Attain-Align-Integrate (A2I) is a model for teacher educators to create short-term training programmes (STTP) to achieve constructive alignment in use of Information and Communication Technology. In this paper we describe the model, its key features, then the instantiation of the model as a STTP. Following this, the evaluation of the STTP is described to explain the utility of the model for attaining faculty professional development goals. The results of STTP indicate that participants have shifted from a teachercentric instructional strategy to a student-centered one, however they require more practice in the alignment to integrate it completely within their teaching learning environment.

Think-pair-share (TPS) is a classroom active learning strategy in which students work on activities, first individually, then in pairs and finally as the whole class. TPS allows students to express their reasoning, reflect on their understanding and obtain prompt feedback on their learning. While TPS is recommended to foster classroom engagement and learning, there is a lack of research based evidence in computer science education on the benefits of TPS for learning. In this study, we investigate the learning effectiveness of TPS in a CS1 course. We performed a quasi-experimental study and found that students who learned via TPS performed significantly better on a post-test than students who learned the same concept via lecture. We also conducted a survey and focus group interviews to understand student perceptions of learning with TPS. The majority of students agreed that TPS activities helped improve their conceptual understanding. From an instructor's point of view, TPS was useful to address the challenges of a large class, such as students tuning out or getting distracted and was easy to implement even in a large class.

The query-model or decision-tree model is a computational model in which the algorithm has to solve a given problem by making a sequence of queries which have 'Yes' or 'No' answers. A large class of algorithms can be described on this model and we can also prove non-trivial lower bounds for many problems on this model.

The extremality principle is one of the commonly used problem solving strategies. It involves looking at the extremal cases of a problem in order to obtain insight about the general structure. Though the principle is widely known, its use in designing algorithms is rarely discussed in CS literature. We present a methodology based on the extremality principle that is useful in solving a wide variety of algorithmic problems. We illustrate the effectiveness of the methodology by deriving solutions to three difficult problems. We believe that the key steps involved in our methodology can be taught to students as individual drills. We have anecdotal evidence for the teachability of the method.

A large CS1 class often needs to provide scaffolding for novices while keeping advanced learners engaged. Scratch has been shown to be suitable to address a diverse set of requirements. In this study, we determine whether a 2-week Scratch intervention in a CS1 course is useful from two perspectives: i) as a scaffold for novices to learn basic programming concepts and transition to C++, and ii) as a tool for advanced learners to remain engaged and do challenging work. We conducted a field study of 332 first-year undergraduate engineering students, two-thirds of whom were novices. We analyzed student performance on exams and Scratch projects. We administered a survey to determine student perceptions on the usefulness of Scratch. Some key findings of our study are: (i) Novices were able to catch-up to advanced learners in Scratch questions of the type 'Predict the output' and 'Debug the program', (ii) Projects by advanced learners reached 80% of the complexity of 'most loved projects' on the Scratch website, and (iii) 69% of students perceived Scratch to be useful for learning programming concepts and transitioning to C++.

Visualizations in computer science topics are known to have several benefits such as promoting conceptual and procedural understanding, improving prediction and reasoning abilities and helping learners construct mental models. This learning effectiveness has been found to be a function of students’ engagement level with visualization. In the current study, we did a controlled field experiment to determine the effect of two different instructional strategies with visualization on procedural understanding of the topic of pointers in a 1st year programming classroom. These instructional strategies, operationalizing different engagement levels, were: prediction activity interleaved with instructor feedback using visualization (experimental), and simply viewing the visualization with parallel instructor commentary (control). We found significant difference in the relative rate of correct solution of the procedural questions on the post-test. However, there was no significant difference on the post-test scores. We also found a significant difference in classroom behavioral engagement between the two groups. We propose that there may be conditions, other than engagement level with visualization, such as learner characteristics or challenge level of assessment questions that may play a role in the determining learning effectiveness of visualizations.

Students find Computer Graphics concepts of transformations difficult to visualize. Using Blender 3D, we developed a three-hour training module on solving transformations problems. We used think-aloud method and conducted interviews for data collection. Analysis of results suggests that, students found training module beneficial to visualize and solve transformations.

Teach 10000 Teachers is a project supported by the Government of India for training large numbers college instructors through distance education. The mode used is Synchronous Remote Classrooms (SRC), in which lectures are transmitted from a single location and participants attend them synchronously in their respective classrooms. In this paper we present a model for adapting well-known active learning (AL) strategies from face-to-face classrooms to the SRC mode, so as to enable effective learning. Our model identifies three levels of interactions – student-content, student-student and student-instructor – and then adapts these interactions to the SRC mode, using the affordances of the technology. We implemented this model with five AL strategies, in a 1-week workshop. We validated the model by examining participants' perception of the effectiveness of the AL strategies for their learning and engagement. We found that 86% of 1287 participants found our adapted AL strategies to be useful in learning. We also found that there is a high correlation (γ=0.75 ) between the perceptions of overall satisfaction and usefulness of AL strategies.

Think-Pair-Share (TPS) is a classroom-based active learning strategy, in which students work on a problem posed by the instructor, first individually, then in pairs, and finally as a class-wide discussion. TPS has been recommended for its benefits of allowing students to express their reasoning, reflect on their thinking, and obtain immediate feedback on their understanding. While TPS is intended to promote student engagement, there is a need for research based evidence on the nature of this engagement. In this study, we investigate the quantity and quality of student engagement in a large CS1 class during the implementation of TPS activities. We did classroom observations of students over a period of ten weeks and thirteen TPS activities. We determined patterns of student engagement in the three phases using a real-time classroom observation protocol that we developed and validated. We found that 83% of students on average were fully or mostly engaged. Predominant behaviors displayed were writing the solution to the problem (Think), discussing with neighbor or writing (Pair), and following class discussion (Share). We triangulated results with survey data of student perceptions. We find that students report being highly engaged for 62% during Think phase and 70% during Pair phase.

The goals of a typical Networking course for Computer Science majors include getting students to learn the relevant concepts, delving into details of various protocols, and using Networking utilities. Such focus on low-level details is unlikely to be interesting to non-majors. Also, there is a larger danger of students not understanding the basic concepts due to the perceived complexity in the details and technical jargon. We address both these issues by teaching Networking concepts through solving problems in analogical real-life scenarios. The main idea of our approach is: The instructor poses an analogy problem, students work in groups to devise solutions, followed by a class discussion to map the analogy problem as well as its solution to their corresponding technical details in Networking domain. Thus we emphasize the core concepts of Networking and demystify the specialized technical details. Across three offerings of this course, we have found that: (i) our students' performance on typical Networking questions is comparable or higher than traditionally taught students, (ii) students can solve unseen technical problems, (iii) students' confidence in tackling technical questions is high.

In Intelligent Tutoring Systems, affect-based computing is an important research area. Common approaches to deal with the affective state identification are based on input data from external sensors such as eye-tracker and EEG, as well as methods based on mining of ITS log data. Sensor based methods are viable in laboratory settings but they are tough to implement in real-world scenario which might cater to a large number of students. In our research, we create a mathematical model of frustration based on its theoretical definition. We identify the variables in the model by applying the theoretical definition of frustration to the ITS log data. This approach is different from existing data mining techniques, which use correlation analysis with labeled data. We apply our model to Mindspark, a commercial maths Intelligent Tutoring System, used by several thousand students. We validate our model with human observations of frustration.

Problem solving is the focus of any algorithm design course. Being able to construct counterexamples is a critical part of the problem solving process. We address the following question: Is there a teachable approach to construct counterexamples? We present a technique, called the Anchor Method, that could prove useful in constructing counterexamples for greedy algorithms. The basic idea of the method is to get insight about the structure of a counterexample by weakening the greedy algorithm. We show the applicability of the method by constructing counterexamples for some classic problems in graph theory. We also investigate the teachability of the technique through experiments.

Significant investments are being made into distance education programs around the world. Yet there is no clear understanding of the effectiveness of such programs, or what makes a distance education program successful. This is in part because the analysis of a distance education program involves studying the behaviour of a complex interactive system. It is therefore worthwhile identifying a suitable tool for a theoretical study of such systems. One such tool is system dynamics modeling, a powerful approach to understand the behaviour of a complex system over time. In this paper, we present a system dynamics simulation model of a distance education program at a leading engineering institute in India. We describe how the model is constructed from the individual components of the program and how a system dynamics approach is used to analyze the program. The results of the simulations helped us plan future investments of the distance education program.

We investigate the issue of automated design of wireless mesh networks (WMN). The general scenario we envision is that of constructing WMNs with WLAN networks as clients (tier 1) and a mesh network (tier 2) to provide inter-WLAN as well as gateway connectivity. Our main aim in this work is to a) design capacity-constrained WMNs, b) build resilient WMNs with transient demands.

We consider multimedia applications where clients specify a minimum desired stream rate (quality) and a time till when they are willing to wait, termed delay tolerance. The content service provider's (CSP) objective is to service as many clients' requests for the same multimedia content with a single stream while satisfying their requirements. We propose an optimization approach to determine the rates delivered at clients and study three transcoder deployment strategies: (i) Source transcoding (ST): when content encoded at different rates are available only at the source (ii) Anywhere transcoding (AT): when transcoding capability is available at all intermediate nodes, and (iii) Selected node transcoding (SNT): when transcoding capability is available at selected intermediate nodes. Considering the complexity of the optimal solution, we propose a set of heuristic based algorithms for delivering enhanced rates to clients using the three strategies. A practical content dissemination network is used to demonstrate the effectiveness of our strategies

Distributed infrastructures are becoming more and more diverse in nature. An application may often need to be redeployed in various scenarios. Ideally, given an application designed for one deployment scenario, one should be able to generate an application version for a new scenario through an automated refactoring process. For this to happen, one of the principal requirements is that application components should be amenable to partitioning. To achieve this: (i) We use a structurally simple and slightly modified model of object called breakable object (BoB), for structuring such applications. BoB can be treated as an object which is designed to be well disposed towards automated refactoring. We also devise a programming model for BoBs in Java called Java/sub BoB/. (ii) We provide algorithms for automated refactoring of a Java/sub BoB/ based program.

No abstract available.

This paper proposes the concept of Breakable Objects (BoBs) as the building blocks for flexible application architectures. We claim that BoB Driven Architecture (BODA) greatly facilitates automated refactoring of an application for various deployment scenarios.

The enhancements to the IEEE 802.11 DCF MAC protocol which enable nodes to identify themselves as exposed nodes and to opportunistically schedule concurrent transmissions whenever possible, thereby improving utilization and mitigating the exposed node problem are described. The algorithm makes minimal changes to the IEEE 802.11 MAC protocol. It does not require the introduction of new frame types or changes to existing frame formats. We show, using simulations in GloMoSim, that it provides significant improvement in throughput.

The object-oriented paradigm in software engineering provides support for the construction of modular and reusable program components and is attractive for the design of large and complex distributed systems. Reachability analysis is an important and well-known tool for static analysis of critical properties in concurrent programs, such as deadlock freedom. It involves the systematic enumeration of all possible global states of program execution and provides the same level of assurance for properties of the synchronization structure in concurrent programs, such as formal verification. However, direct application of traditional reachability analysis to concurrent object-oriented programs has many problems, such as incomplete analysis for reusable classes (not safe) and increased computational complexity (not efficient). We propose a novel technique called apportioning, for safe and efficient reachability analysis of concurrent object-oriented programs, that is based upon a simple but powerful idea of classification of program analysis points as local (having influence within a class) and global (having possible influence outside a class). We have developed a number of apportioning-based algorithms, having different degrees of safety and efficiency. We present the details of one of these algorithms, formally show its safety for an appropriate class of programs, and present experimental results to demonstrate its efficiency for various examples.

The object-oriented paradigm has been found to be useful for the construction of large and complex concurrent systems. Reachability analysis is an important and well-known tool for static (pre-run-time) analysis of concurrent programs. However, direct application of traditional reachability analysis to concurrent object-oriented programs has many problems, such as incomplete analysis for reusable classes (not safe) and increased computational complexity (not efficient). We have proposed a novel technique called apportioning, for effective reachability analysis of concurrent object-oriented programs, that integrates the techniques of abstraction (considering a reduced representation of the system) and partitioning (dividing the system into smaller units). The given program is apportioned into a reduced version of each of its classes, as well as a reduced version of the program. The error to be checked is also decomposed into appropriate sub-properties for checking in the reachability graphs corresponding to the apportioned program. We have developed a number of apportioning-based algorithms, having different degrees of safety and effectiveness. In this paper, we present the details of one of these algorithms.

The object-oriented paradigm provides support for modular and reusable design and is attractive for the construction of large and complex concurrent systems. Reachability analysis is an important and well-known tool for static (pre-run-time) analysis of concurrent programs. However its direct application to concurrent object-oriented programs has many problems, such as incomplete analysis for reusable classes and increased computational complexity. It also seems impossible to arrive at a single general-purpose strategy that is both safe and effective for all programs. The authors propose a tool-suite based approach for the reachability analysis of concurrent object-oriented-programs. This approach enables choice of an appropriate 'ideal' tool, for the given program and also provides the flexibility for incorporation of additional tools. They have also proposed a novel abstraction-based partitioning methodology for effective reachability analysis of concurrent object-oriented programs. Using this methodology, they have developed a variety of tools, having different degrees of safety, effectiveness and efficiency, for incorporation into the tool-suite. They have formally shown the safety of these tools for appropriate classes of programs and have evaluated their effectiveness and efficiency.