Search

Cognitive engagement, a complex concept in the field of education, has a great impact on student learning that can be assessed using facial expression analysis. Facial expression analysis uses visual information to detect and recognize human emotions as a measure of student's cognitive engagement, particularly during problem-solving activities. This systematized literature review explores the empirical literature to understand the relationships between students' cognitive engagement levels and human emotions to highlight the different phases of engagement levels concerning problem-solving tasks and corresponding emotions (that act as potential indicators of deeper cognitive engagement). It is essential to quantify the cognitive engagement level to assess the efficacy of the educational strategies, cognitive skills, and motor skills in terms of learning outcomes. However, while the available literature reviews offer summaries of various cognitive engagement techniques and their impacts, they neglect to synthesize the technical aspects of emerging technologies and trends that may provide useful associations between cognitive engagement in educational settings and emotions-based facial expressions. In this literature review, we have identified significant associations between students' cognitive engagement during problem-solving tasks and facial expressions. The nuanced analysis of facial cues reveals key indicators of heightened cognitive engagement, such as expressions of curiosity, excitement, concentration, determination, and satisfaction. These emotions are proposed as valuable markers for deeper cognitive engagement in educational contexts. By synthesizing the existing research, this review sheds light on how students' cognitive engagement is associated with visible facial expressions, and how facial expressions can help educators comprehend students' engagement levels in real-time. This review also reveals the emotions associated with underlying cognitive processes to improve instruction teaching and learning and personalized learning. Last, this review further seeks to highlight gaps that can guide future research. This systematic literature review explores one potential cause of the lack of student engagement in education settings, and visible expressions associated with engagement through systematic analysis of literature. Findings from this review will be used to advance pedagogy and educational strategies to advance the student-centered educational environment. [ABSTRACT FROM AUTHOR]

This paper shares the initial findings of a three-year research project. Quantitative methods were used to develop coarse-grained understandings of undergraduate students' self-regulation of cognition (SRC) and self-regulation of motivation (SRM) during academic problem-solving activities in two undergraduate engineering and mathematics (EM) courses. Two research questions were constructed to guide this study: (1) How are SRC and SRM strategies related to each other while solving EM problems?; and (2) How do students perceive their SRC and SRM strategies for problem-solving activities in EM courses?. Two 2nd year EM courses, Engineering Statics and Ordinary Differential Equations, were purposefully selected as the contexts of the study. There were a combined total of 142 students (120 male and 20 female), across both courses, that participated in quantitative data collection using two validated surveys during spring 2022. Quantitative data were collected using two selfreport surveys: Brief Regulation of Motivation Scale (BRoMS), and the Physics Metacognitive Inventory (PMI). Although PMI was initially designed for Physics, it can be used to assess students' metacognition for problem solving in other knowledge domains by simply revising the word "physics" to another domain knowledge. Both descriptive and inferential statistics were conducted to analyze the collected quantitative data. During data analysis we found: (1) a significant relationship between students' strategies to selfregulate their cognition and motivation during EM problem-solving activities; (2) no significant difference between male and female's self-regulation of cognition (SRC) and self-regulation of motivation (SRM); (3) no significant difference of SRM between students who engaged in Engineering Statics and Ordinary Differential Equation problem-solving activities; and (4) a significant difference of reported strategies in interpreting problem and evaluating strategies between those who engaged in Engineering Statics and Ordinary Differential Equation problemsolving activities. Participants reported using certain SRM strategies, such as "If I need to, I have ways of convincing myself to keep working on a tough assignment" more frequently than other strategies during problem solving. [ABSTRACT FROM AUTHOR]

This work-in-progress paper shares findings of the early stage of a 3-year research funded by the National Science Foundation. The major aim of the project is to advance engineering and mathematics (EM) education theory and practice related to students' self-regulation of cognition and motivation skills during problem-solving activities. The self-regulation includes students' metacognitive knowledge about task (MKT) and self-regulation of cognition (SRC). The motivational component of self-regulation (SRM) includes self-control of the motivation needed to maintain the level of engagement and deliberate practice necessary for scientific thinking and reasoning. To be effective problem-solvers, students must understand the relationship between the MKT, SRC and SRM throughout the problem-solving activities. Four research questions will guide the research: (1) How do students perceive their self-regulation of cognition (SRC) and motivation (SRM) skills for generic problem-solving activities in EM courses; (2) How does students' metacognitive knowledge about problem-solving tasks (MKT) inform their Task interpretation?; (3) How do students' SRC and SRM dynamically evolve?; and (4) How do students' SRC and SRM reflect their perceptions of self-regulation of cognition and motivation for generic EM problemsolving activities?. A sequential mixed-methods research design involving quantitative and qualitative methods are used to develop complementary coarse- and fine-grained understandings of undergraduate students' SRC and SRM during academic problem-solving activities. Two 2nd year EM courses: Engineering Statics, and Ordinary Differential Equations were purposefully selected for the contexts of the study. One hundred forty two students from both courses were invited and participated in quantitative data collection using two validated surveys during spring 2022 semester. Later in the semester, qualitative data will be generated with twenty students in both courses through one-on-one interviews with students and course instructors, think-aloud protocols with students, and classroom observations. Coarse-grained understandings of students' SRC and SRM are currently developed through analysis of quantitative data collected using self-report surveys (i.e., BRoMS and PMI). Fine-grained understandings of students' SRC and SRM will be developed through analysis of qualitative data gathered via one-on-one interviews, think-aloud protocols, classroom observations, and course artifacts gathered as students engage in EM problem-solving activities. [ABSTRACT FROM AUTHOR]

This paper reports preliminary findings from a National Science Foundation (NSF) funded research targeting enhancing Engineering and Mathematics (EM) education. The project's central objective is to explain the critical role of students' metacognitive knowledge about task (MKT) and self-regulation in action (SRA) during problem-solving activities. This research paper seeks to understand the interplay between MKT and SRA, and how it leads to their problem-solving performance in two second-year engineering and mathematics (EM) courses, Engineering Statics and Ordinary Differential Equations. Qualitative data were collected through one-on-one interviews before, and think-aloud verbalization while, solving problems. Qualitative data were generated with 20 undergraduate students (i.e., 7 females, and 13 males) across both courses (i.e., 11 and 9 students from mathematics and engineering, respectively) through one-on-one interviews before, and think-aloud verbalization while, solving problems. During data generation, each student engaged in four EM content-driven problem-solving activities of varying levels of difficulty. Data generation resulted in a total of 80 problem-solving qualitative data generation events with 20 unique participants. The qualitative data is analyzed using systematic and iterative techniques based on constant comparative analysis (CCA). Further, the analysis involves the deployment of initial and focused level codes, where initial codes directly reflect the raw data, while focused codes refine the seven significant problem-solving cases or patterns observed across the dataset. Based on the analysis, the seven cases were clustered into four quadrants based on their low/high MKT level and low/high SRA levels. Each case describes a unique interplay between students' knowledge about tasks and self-regulation. In this paper, we focus on two possible cases belonging to the second quadrant (i.e., Adaptive Learning, and Faulty Adaptive Learning). In the adaptive learning environment, effective self-regulating deployment could enhance students' inadequate metacognitive knowledge about tasks to achieve satisfactory task performance. Faulty adaptive illustrates a problem-solving episode where adequate self-regulating strategies with a lack of metacognitive knowledge about tasks could also potentially lead to unsatisfactory task performance. A brief discussion is included at the end of the paper. [ABSTRACT FROM AUTHOR]

The profound impact of cognitive factors on student's performance while solving complex and ill-structured problems is well recognized. A student's success in problem-solving is finely shaped by task complexity, cognitive factors of goal orientation and the need for cognitive closure, and their level of engagement. For educators in science, technology, engineering, and mathematics (STEM), it is important to understand how task complexity and cognitive factors combine to influence problem-solving processes to prepare STEM students professionally and ensure they are well-equipped to meet the growing needs of the skilled workforce in the industry. In this context, cognitive factors of goal orientation and the need for cognitive closure play a significant role. An extensive body of research has yielded diverse findings and insights and has explored the relationship between task complexity, cognitive factors of goal orientation, and the need for cognitive closure, and their combined impact on student engagement in the context of STEM education. This growing body of research emphasizes the need for a comprehensive synthesis and analysis of existing literature to utilize the wealth of knowledge productively that has developed over time. By analyzing the existing literature comprehensively, this systematized literature review addresses the influence of task complexity on the cognitive factors of goal orientation and the need for cognitive closure and students' engagement during problem-solving in STEM education. Resultant themes central to the research questions are being developed using qualitative data analysis techniques. By synthesizing the existing research, this review sheds light on how the student's cognitive responses are influenced by different levels of task complexity during problem-solving and how the task complexity enhances or hinders student's engagement in STEM education. [ABSTRACT FROM AUTHOR]

This work-in-progress paper shares findings of the early stage of a 3-year research funded by the National Science Foundation. The major aim of the project is to advance engineering and mathematics (EM) education theory and practice related to students' self-regulation of cognition and motivation skills during problem-solving activities. The self-regulation includes students' metacognitive knowledge about task (MKT) and self-regulation of cognition (SRC). The motivational component of self-regulation (SRM) includes self-control of the motivation needed to maintain the level of engagement and deliberate practice necessary for scientific thinking and reasoning. To be effective problem-solvers, students must understand the relationship between the MKT, SRC and SRM throughout the problem-solving activities. Four research questions will guide the research: (1) How do students perceive their self-regulation of cognition (SRC) and motivation (SRM) skills for generic problem-solving activities in EM courses; (2) How does students' metacognitive knowledge about problem-solving tasks (MKT) inform their Task interpretation?; (3) How do students' SRC and SRM dynamically evolve?; and (4) How do students' SRC and SRM reflect their perceptions of self-regulation of cognition and motivation for generic EM problemsolving activities? A sequential mixed-methods research design involving quantitative and qualitative methods are used to develop complementary coarse- and fine-grained understandings of undergraduate students' SRC and SRM during academic problem-solving activities. Two 2nd year EM courses: Engineering Statics, and Ordinary Differential Equations were purposefully selected for the contexts of the study. One hundred forty two students from both courses were invited and participated in quantitative data collection using two validated surveys during spring 2022 semester. Later in the semester, qualitative data will be generated with twenty students in both courses through one-on-one interviews with students and course instructors, think-aloud protocols with students, and classroom observations. Coarse-grained understandings of students' SRC and SRM are currently developed through analysis of quantitative data collected using self-report surveys (i.e., BRoMS and PMI). Fine-grained understandings of students' SRC and SRM will be developed through analysis of qualitative data gathered via one-on-one interviews, think-aloud protocols, classroom observations, and course artifacts gathered as students engage in EM problem-solving activities. [ABSTRACT FROM AUTHOR]

Domain Name System (DNS) is the vital part of the internet world. One of the attacks on DNS is an amplification attack, in which IP is spoofed by the eavesdropper in order to launch a bandwidth consumption attack. In this attack Bulk of responses are received by the victim server in a response to a single query. In this paper the structure of the Bloom Filter is modified and its defense against the amplification attack is proposed. In this proposed solution, we used a modified bloom filter in which we have added one more property that is, we can edit its membership, such as newcomer, old one and black listed old member. Through this when old members come after a specific interval of time, they are going to register themselves as newcomers in bloom filter and this bloom filter will be placed near the victim ISP or it organization router. So when the attacker initiates a query, after a certain check it can be put on the black list. [ABSTRACT FROM PUBLISHER]

The DNS is one of the most important part of the Internet communication. DNS server runs a robust mechanism which provides the IP address of the internet host name. Even if the any component of this internet communication is unavailable for short interval then the whole internet communication will be disturbed or some time stop responding. When a DNS server sends a query to the specific server then an eves dropper can launch cache poisoning attack easily. Many solutions have been proposed which have their own pros and cones. In this paper a proposed solution is described by using security proxy with a hash function. Cache Poisoning attack can be avoided by using this technique. It creates a secure environment for the DNS to communicate with other DNS. When the source DNS receives any response from any DNS it will check the authenticity of receiving packets and send the data to the client. This technique provides secure environment for DNS communication. This new technique is easy to implement on the current DNS architecture without any modification. [ABSTRACT FROM PUBLISHER]