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Hands-on artificial intelligence with Java for beginners : build intelligent apps using machine learning and deep learning with Deeplearning4j
This book will introduce the AI algorithms to the beginners and will take on implementing AI tasks using various Java-based libraries. It will take a practical approach to get you up and running with building smarter applications using Java programming knowledge.
Book
Multimodal learning analytics of collaborative patterns during pair programming in higher education
Pair programming (PP), as a mode of collaborative problem solving (CPS) in computer programming education, asks two students work in a pair to co-construct knowledge and solve problems. Considering the complex multimodality of pair programming caused by students’ discourses, behaviors, and socio-emotions, it is of critical importance to examine their collaborative patterns from a holistic, multimodal, dynamic perspective. But there is a lack of research investigating the collaborative patterns generated by the multimodality. This research applied multimodal learning analytics (MMLA) to collect 19 undergraduate student pairs’ multimodal process and products data to examine different collaborative patterns based on the quantitative, structural, and transitional characteristics. The results revealed four collaborative patterns (i.e., a consensus-achieved pattern, an argumentation-driven pattern, an individual-oriented pattern, and a trial-and-error pattern), associated with different levels of process and summative performances. Theoretical, pedagogical, and analytical implications were provided to guide the future research and practice.
Journal Article
A review of AI teaching and learning from 2000 to 2020
In recent years, with the popularity of AI technologies in our everyday life, researchers have begun to discuss an emerging term “AI literacy”. However, there is a lack of review to understand how AI teaching and learning (AITL) research looks like over the past two decades to provide the research basis for AI literacy education. To summarize the empirical findings from the literature, this systematic literature review conducts a thematic and content analysis of 49 publications from 2000 to 2020 to pave the way for recent AI literacy education. The related pedagogical models, teaching tools and challenges identified help set the stage for today’s AI literacy. The results show that AITL focused more on computer science education at the university level before 2021. Teaching AI had not become popular in K-12 classrooms at that time due to a lack of age-appropriate teaching tools for scaffolding support. However, the pedagogies learnt from the review are valuable for educators to reflect how they should develop students’ AI literacy today. Educators have adopted collaborative project-based learning approaches, featuring activities like software development, problem-solving, tinkering with robots, and using game elements. However, most of the activities require programming prerequisites and are not ready to scaffold students’ AI understandings. With suitable teaching tools and pedagogical support in recent years, teaching AI shifts from technology-oriented to interdisciplinary design. Moreover, global initiatives have started to include AI literacy in the latest educational standards and strategic initiatives. These findings provide a research foundation to inform educators and researchers the growth of AI literacy education that can help them to design pedagogical strategies and curricula that use suitable technologies to better prepare students to become responsible educated citizens for today’s growing AI economy.
Journal Article
Heads-up limit hold'em poker is solved
Poker is a family of games that exhibit imperfect information, where players do not have full knowledge of past events. Whereas many perfect-information games have been solved (e.g., Connect Four and checkers), no nontrivial imperfect-information game played competitively by humans has previously been solved. Here, we announce that heads-up limit Texas hold'em is now essentially weakly solved. Furthermore, this computation formally proves the common wisdom that the dealer in the game holds a substantial advantage. This result was enabled by a new algorithm, CFR+, which is capable of solving extensive-form games orders of magnitude larger than previously possible.
Journal Article
Computational thinking development through creative programming in higher education
Creative and problem-solving competencies are part of the so-called twenty-first century skills. The creative use of digital technologies to solve problems is also related to computational thinking as a set of cognitive and metacognitive strategies in which the learner is engaged in an active design and creation process and mobilized computational concepts and methods. At different educational levels, computational thinking can be developed and assessed through solving ill-defined problems. This paper introduces computational thinking in the context of Higher Education creative programming activities. In this study, we engage undergraduate students in a creative programming activity using Scratch. Then, we analyze the computational thinking scores of an automatic analysis tool and the human assessment of the creative programming projects. Results suggested the need for a human assessment of creative programming while pointing the limits of an automated analytical tool, which does not reflect the creative diversity of the Scratch projects and overrates algorithmic complexity.
Journal Article
Can CPS better prepare 8th graders for problem-solving in electromagnetism and bridging the gap between high- and low-achievers than IPS?
The individual problem-solving (IPS) and collaborative problem-solving (CPS) have received a lot of attention, yet little research has been conducted to investigate whether CPS and IPS are equally effective in improving students’ understanding of physics concepts, problem-solving abilities, and minimizing achievement gaps. Therefore, the present study developed two types of online electromagnetism problem solving programs with simulation—IPS and CPS—for 8th grade students over five class sessions. Students in the CPS group significantly outperformed those in the IPS group on their performance of physics problem solving test and online problem-solving solution, while IPS and CPS both affected their physics concept test performance to the same degree. The CPS group allocated more time to the online problem-solving solution, evidence-based reasoning, simulation and data reporting than the IPS group. Both CPS and IPS affected high-achievers' problem-solving performance to the same extent. Nonetheless, CPS was more effective in maximizing low-achievers' problem-solving performance and minimizing the discrepancy between high- and low-achievers than IPS, possibly because low-achievers in CPS group requested and received more support from high-achieving students. Regression analysis indicated that students' online problem-solving solution significantly predict their posttest performance in the physics concept test and physics problem-solving test.
Journal Article
Examining primary students’ mathematical problem-solving in a programming context: towards computationally enhanced mathematics education
This paper reports on a design-based study within the context of a 3-day
digital making
(DM) summer camp attended by a group of students (aged 11–13) in grades 5 and 6. During the camp, students were presented with a set of mathematical problems to solve in a block-based programming environment, which was connected to various physical input sensors and output devices (e.g., push buttons, LED lights, number displays, etc.). Students’ code files, and screen captures of their computer work, were analyzed in terms of their developed computational problem-solving practices and any computational concepts that emerged during the problem-based DM. The results suggested that the designed tasks consistently supported the students’ modeling and algorithmic thinking, while also occasioning their testing and debugging practices; moreover, the students utilized computational abstractions in the form of variables, and employed different approaches, to formulate mathematical models in a programming context. This study contributes to the ‘big picture’ of how using computers might fundamentally change mathematics learning, with an emphasis on mathematical problem-solving. It also provides empirically grounded evidence to enhance the potential of computational thinking as a new literacy, and problem-solving as a global competence, in formal school settings.
Journal Article
Coding as a Playground
Coding as a Playground, Second Edition focuses on how young children (aged 7 and under) can engage in computational thinking and be taught to become computer programmers, a process that can increase both their cognitive and social-emotional skills. Learn how coding can engage children as producers-and not merely consumers-of technology in a playful way. You will come away from this groundbreaking work with an understanding of how coding promotes developmentally appropriate experiences such as problem-solving, imagination, cognitive challenges, social interactions, motor skills development, emotional exploration, and making different choices. Featuring all-new case studies, vignettes, and projects, as well as an expanded focus on teaching coding as a new literacy, this second edition helps you to learn how to integrate coding into different curricular areas to promote literacy, math, science, engineering, and the arts through a project-based approach and a positive attitude to learning.
eBook
Teaching Problem Solving Skills using an Educational Game in a Computer Programming Course
Problem solving skills are considered an important component in learning to program in an introductory programming (IP) course for novices. This study introduced a PROSOLVE game to enhance problem solving skills of novice programmers in the introductory programming course. The game is based on pseudo-code technique. A survey was employed to collect students' feedback and semi-structured interviews were organized to collect instructors' opinion about the game. The results show that the game helped most of the students in understanding the programming concepts, structures and problem solving strategies. Moreover, the game supports students' cognitive engagement, gains, and affective engagement in the IP course. Instructors appreciated the game and considered it as an additional supporting teaching tool in the IP course. Moreover, they considered the game as good alternative of traditional pen and paper learning approach in attracting students' interest in the programming domain.
Journal Article
Interactions with generative AI chatbots: unveiling dialogic dynamics, students’ perceptions, and practical competencies in creative problem-solving
This study explores the effectiveness of chatbots empowered by generative artificial intelligence (GAI) in assisting university students’ creative problem-solving (CPS). We used quasi-experiments to compare the performance of dialogue dynamics, learner perceptions, and practical competencies in CPS during students’ interactions with: (1) a GAI chatbot, and (2) their peers. In total, 80 postgraduate students participated. The assigned CPS task was the creation of an innovative research proposal. We found that there were significant differences in the dialogic exchanges observed between the two types of interaction. Student-GAI chatbot interactions featured more knowledge-based dialogue and elaborate discussions, with less subjective expression compared to student-peer interactions. Notably, students contributed significantly less dialogue when interacting with a GAI chatbot than they did during peer interactions. The dialogic exchanges arising from student-GAI chatbot interactions tended to follow distinct patterns, while those from student-peer interactions were less predictable. The students perceived interacting with a GAI chatbot as more useful and easier than interacting with peers. Furthermore, they exhibited higher intention levels when utilising a GAI chatbot to tackle the CPS task compared to engaging in discussions with their peers. Ultimately, practical performance was significantly enhanced through interactions with a GAI chatbot. This study implies that the prudent use of GAI-based techniques can facilitate university students’ learning achievement.
Journal Article