Redcay’s STEM-oscope Model: Connecting STEM Education, Social Robots, and Metacognition

A qualitative analysis of second grade students’ responses to Science, Technology, Engineering, and Mathematics (STEM) Challenge demonstrated that young learners use metacognitive skills throughout challenges (beginning, middle, and end). Students work through Engineer by Design (EbD) loop: (1) define and research a problem (2) brainstorm and explore possible solutions (3) develop a prototype (4) test (5) reflect (6) redesign (7) re-test. Social robots can be used throughout STEM challenges to model think alouds. Educators prepare the environment for young learners. Specially, educators find meaningful ways for students to connect concrete and abstract ideas. Five themes emerged from students’ responses to two STEM challenges. The theme with the highest frequency demonstrated that students were making real-world connections. The additional themes included metalinguistic awareness, problem solving strategies, social metacognitive thinking, and concrete to abstract thinking. The five themes were connected to metacognitive thinking, EbD loop, and 6 E’s of Science Inquiry. The themes were arranged in a new model called Redcay’s STEM-oscope Model used to describe the connection between STEM education, social robots, and metacognition. The research study adds to the existing body of research about STEM education by directly linking metacognitive skills, STEM education, social robots

Exploring the Learning Gains of Implementing Teacher Humanoid Robots in STEM Education: A Systematic Review

Εducational (or pedagogical) robotics has received increased attention over the last few years based on its effectiveness on the learning process. Humanoid robots have been recently introduced in school settings to mainly support teaching of curriculum-based subjects. However, humanoid robots’ benefits on STEM education in typical classroom settings are less examined by the research literature. Instead, most research studies take place in non-typical school or classroom settings (such as laboratories). The main goal of the current review is to sum up results of relevant research studies about the positive impact of teacher humanoid robots on STEM education. The learning benefits in STEM subjects, programming and reasoning skills are examined too. Sample subject of this review are mainstream students aged 4 to 18 years old and research studies are grouped based on their commonalities such as common learning areas and results

A systematic review of the literature regarding socially assistive robots in pre-tertiary education

With rapid advances in Artificial Intelligence (AI) over the last decade, schools have increasingly employed innovative tools, intelligent applications and methods that are changing the education system with the aim of improving both user experience and learning gain in the classrooms. Even though the use of AI to education is not new, it has not unleashed its full potential yet. Much of the available research looks at educational robotics and at non-intelligent robots in education. Only recently, research has sought to assess the potential of Socially Assistive Robots (SARs), including humanoids, within the domain of classroom learning, particularly in relation to learning languages. Yet, the use of this form of AI in the field of mathematics and science constitutes a notable gap in this field. This study aims to critically review the research on the use of SARs in the pre-tertiary classroom teaching of mathematics and science. Further aim is to identify the benefits disadvantages of such technology. Databases' search conducted between January and April 2018 yielded twenty-one studies meeting the set inclusion criteria for our systematic review. Findings were grouped into four major categories synthesising current evidence of the contribution of SARs in pre- tertiary education: learning gain, user experience, attitude, and usability of SARs within classroom settings. Overall, the use of SARs in pre-tertiary education is promising, but studies focussing on mathematics and science are significantly under-represented. Further evidence is also required around SARs' specific contributions to learning more broadly, as well as enabling/impeding factors, such as SAR's personalisation and appearance, or the role of families and ethical considerations. Finally, SARs potential to enhance accessibility and inclusivity of multi-cultural pre-tertiary classroom is almost unexplored

Read and Lead: Fostering Literacy through Cross-Age Tutoring (Facilitator\u27s Manual To Implement a National Literacy Corps)

Congratulations on choosing the Read & Lead Facilitator\u27s Guide for your cross-age tutoring program! This guide is designed to help you facilitate a National Literacy Corps in your own school, after school program, organization, or community. The National Literacy Corps began in Philadelphia high schools in 1991. Since that time the National Literacy Corps model has been implemented in schools across the country and in England. The National Literacy Corps was recognized as an exemplary model at the President\u27s Summit on America\u27s Future in April 1997. Since 2000, the model has been modified for successful implementation in middle and upper elementary grades as well as an innovative model for college work study, after school, and community based programs. Hundreds of AmeriCorps members have used these resources to train youth as Leaders, to break the cycle of illiteracy in local communities. Read & Lead, the National Literacy Corps cross-age tutoring model incorporates civic engagement and work place readiness skills into an effective literacy based service-learning model. Good citizens are literate, well informed, and know how to address a problem in their community. To be ready for the world of work young people must be able to work well with others, take a leadership role when necessary, and plan and carry out the steps required to reach a final goal. As such, program participants in the National Literacy Corps study literacy as a community issue and design a service-learning project to meet a community need. At the same time, youth who may themselves be at-risk engage in a one on one relationship to increase the literacy level of a young child

Reasoning, argumentative interaction and idea life cycles during group product ideation in higher education

Abstract. This study presents the analysis of the use of argument in group ideation process in higher education settings. The need for such analysis is dictated by the fact that students in higher education are one step away from joining wider professional communities, where the ability to engage in joint brainstorming and evaluating new products is in high demand. The study data consists of transcripts of ideation discussions of two groups of master’s degree students. The task for both groups was to imagine and formulate a future AI-based teaching/learning assistant, prepare a short verbal presentation of the product, and present it to the whole class. The analysis is arranged in three steps. First, frequency and quality of grounded claims is evaluated using Toulmin’s Argumentation Pattern. Then, the type of talk is determined using the indicators of exploratory, cumulative and disputational talk (Mercer, 1996), the interplay between types of talk is examined. Finally, idea life cycles and reasoning behind idea demotion is investigated. The results indicate that 1) arguments are provided rarely, but when provided, most of them (2/3) are complete; 2) exploratory talk manifests mostly in elaborations on peers’ ideas, whereas reasoning (justifications) to own ideas and critical evaluation is less frequent; these factors characterise the discussions more as co-constructive interaction rather than exploratory talk; 3) dominance of elaborative comments on an idea leads to inclusion the idea in group solution; reasoning for idea demotion varies remarkably between the two groups (56% vs. 80%). These outcomes indicate that students might benefit from enhancing their reasoning to be ready for workplace ideation in groups. From task design view, clear product metrics should be set, and a line drawn between brainstorming and evaluation phase, to prevent unreasoned idea demoting in brainstorming and stimulate questioning and reasoning in evaluation

Psychophysiological analysis of a pedagogical agent and robotic peer for individuals with autism spectrum disorders.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder characterized by ongoing problems in social interaction and communication, and engagement in repetitive behaviors. According to Centers for Disease Control and Prevention, an estimated 1 in 68 children in the United States has ASD. Mounting evidence shows that many of these individuals display an interest in social interaction with computers and robots and, in general, feel comfortable spending time in such environments. It is known that the subtlety and unpredictability of people’s social behavior are intimidating and confusing for many individuals with ASD. Computerized learning environments and robots, however, prepare a predictable, dependable, and less complicated environment, where the interaction complexity can be adjusted so as to account for these individuals’ needs. The first phase of this dissertation presents an artificial-intelligence-based tutoring system which uses an interactive computer character as a pedagogical agent (PA) that simulates a human tutor teaching sight word reading to individuals with ASD. This phase examines the efficacy of an instructional package comprised of an autonomous pedagogical agent, automatic speech recognition, and an evidence-based instructional procedure referred to as constant time delay (CTD). A concurrent multiple-baseline across-participants design is used to evaluate the efficacy of intervention. Additionally, post-treatment probes are conducted to assess maintenance and generalization. The results suggest that all three participants acquired and maintained new sight words and demonstrated generalized responding. The second phase of this dissertation describes the augmentation of the tutoring system developed in the first phase with an autonomous humanoid robot which serves the instructional role of a peer for the student. In this tutoring paradigm, the robot adopts a peer metaphor, where its function is to act as a peer. With the introduction of the robotic peer (RP), the traditional dyadic interaction in tutoring systems is augmented to a novel triadic interaction in order to enhance the social richness of the tutoring system, and to facilitate learning through peer observation. This phase evaluates the feasibility and effects of using PA-delivered sight word instruction, based on a CTD procedure, within a small-group arrangement including a student with ASD and the robotic peer. A multiple-probe design across word sets, replicated across three participants, is used to evaluate the efficacy of intervention. The findings illustrate that all three participants acquired, maintained, and generalized all the words targeted for instruction. Furthermore, they learned a high percentage (94.44% on average) of the non-target words exclusively instructed to the RP. The data show that not only did the participants learn nontargeted words by observing the instruction to the RP but they also acquired their target words more efficiently and with less errors by the addition of an observational component to the direct instruction. The third and fourth phases of this dissertation focus on physiology-based modeling of the participants’ affective experiences during naturalistic interaction with the developed tutoring system. While computers and robots have begun to co-exist with humans and cooperatively share various tasks; they are still deficient in interpreting and responding to humans as emotional beings. Wearable biosensors that can be used for computerized emotion recognition offer great potential for addressing this issue. The third phase presents a Bluetooth-enabled eyewear – EmotiGO – for unobtrusive acquisition of a set of physiological signals, i.e., skin conductivity, photoplethysmography, and skin temperature, which can be used as autonomic readouts of emotions. EmotiGO is unobtrusive and sufficiently lightweight to be worn comfortably without interfering with the users’ usual activities. This phase presents the architecture of the device and results from testing that verify its effectiveness against an FDA-approved system for physiological measurement. The fourth and final phase attempts to model the students’ engagement levels using their physiological signals collected with EmotiGO during naturalistic interaction with the tutoring system developed in the second phase. Several physiological indices are extracted from each of the signals. The students’ engagement levels during the interaction with the tutoring system are rated by two trained coders using the video recordings of the instructional sessions. Supervised pattern recognition algorithms are subsequently used to map the physiological indices to the engagement scores. The results indicate that the trained models are successful at classifying participants’ engagement levels with the mean classification accuracy of 86.50%. These models are an important step toward an intelligent tutoring system that can dynamically adapt its pedagogical strategies to the affective needs of learners with ASD