Exploring the Development of Pre-Service Teachers\u27 Knowledge and Attitudes Toward Integrating Computational Thinking and Robotics into the Classroom

This paper presents an introductory computational thinking (CT) module that can be implemented into teacher education curricula. The researchers examined how the integration of CT and robotics instruction into an undergraduate instructional technology course influenced pre-service teachers\u27 understanding of CT and robotics and their attitudes towards adopting these tools in their future classrooms. The online module was developed as a result of a collaboration between computer science and education faculty from two universities. A total of 93 students participated in the study. The course was delivered during the spring, summer, and fall semesters of 2020 via distance learning at a large public university located in Florida. Data for this study were collected using a pre-and post-test survey that was created with Qualtrics software. This paper describes how the CT and robotics concepts were taught and examines the influence of the instruction on participants\u27 knowledge and attitudes of CT and robotics and their integration into the classroom

Task-related models for teaching and assessing iteration learning in high school

A number of studies report about students’ difficulties with basic flow-control constructs, and specifically with iteration. Although such issues are less explored in the context of pre-tertiary education, this seems to be especially the case for high-school programming learning, where the difficulties concern both the “mechanical” features of the notional machine as well as the logical aspects connected with the constructs, ranging from the implications of loop conditions to a more abstract grasp of the underlying algorithms. For these reasons, the aim of this work is to: i) identifying methodological tools to enhance a comprehensive understanding of the iteration constructs, ii) suggest strategies to teach iterations. We interviewed 20 experienced upper secondary teachers of introductory programming in different kinds of schools. The interviews were mainly aimed at ascertaining teachers’ beliefs about major sources of issues for basic programming concepts and their approach to the teaching and learning of iteration constructs. Once teachers’ perception of students’ difficulties have been identified, we have submitted, to a sample of 164 students, a survey which included both questions on their subjective perception of difficulty and simple tasks probing their understanding of iteration. Data collected from teachers and students confirm that iteration is a central programming concept and indicate that the treatment of conditions and nested constructs are major sources of students’ difficulties with iteration. The interviews allowed us to identify a list of problems that are typically presented by teachers to explain the iterations. Hence, a catalogue of significant program examples has been built to support students’ learning, tasks with characteristics different from those typically presented in class. Based on the outcome of previous steps, a survey to collect related information and good practices from a larger sample of teachers has been designed. Data collected have been analysed distinguishing an orientation towards more conceptual objectives, and one towards more practical objectives. Furthermore, regarding evaluation, a orientation focused on process-based assessment and another on product-based assessment. Finally, based on the outcome of previous students’ survey and drawing from the proposed examples catalogue, we have designed and submitted a new students’ survey, composed of a set of small tasks, or tasklets, to investigate in more depth on high-school students’ understanding of iteration in terms of code reading abilities. The chosen tasklets covered the different topics: technical program feature, correlation between tracing effort and abstraction, the role of flow-charts, students’ perception of self-confidence concerning high-level thinking skills.A number of studies report about students’ difficulties with basic flow-control constructs, and specifically with iteration. Although such issues are less explored in the context of pre-tertiary education, this seems to be especially the case for high-school programming learning, where the difficulties concern both the “mechanical” features of the notional machine as well as the logical aspects connected with the constructs, ranging from the implications of loop conditions to a more abstract grasp of the underlying algorithms. For these reasons, the aim of this work is to: i) identifying methodological tools to enhance a comprehensive understanding of the iteration constructs, ii) suggest strategies to teach iterations. We interviewed 20 experienced upper secondary teachers of introductory programming in different kinds of schools. The interviews were mainly aimed at ascertaining teachers’ beliefs about major sources of issues for basic programming concepts and their approach to the teaching and learning of iteration constructs. Once teachers’ perception of students’ difficulties have been identified, we have submitted, to a sample of 164 students, a survey which included both questions on their subjective perception of difficulty and simple tasks probing their understanding of iteration. Data collected from teachers and students confirm that iteration is a central programming concept and indicate that the treatment of conditions and nested constructs are major sources of students’ difficulties with iteration. The interviews allowed us to identify a list of problems that are typically presented by teachers to explain the iterations. Hence, a catalogue of significant program examples has been built to support students’ learning, tasks with characteristics different from those typically presented in class. Based on the outcome of previous steps, a survey to collect related information and good practices from a larger sample of teachers has been designed. Data collected have been analysed distinguishing an orientation towards more conceptual objectives, and one towards more practical objectives. Furthermore, regarding evaluation, a orientation focused on process-based assessment and another on product-based assessment. Finally, based on the outcome of previous students’ survey and drawing from the proposed examples catalogue, we have designed and submitted a new students’ survey, composed of a set of small tasks, or tasklets, to investigate in more depth on high-school students’ understanding of iteration in terms of code reading abilities. The chosen tasklets covered the different topics: technical program feature, correlation between tracing effort and abstraction, the role of flow-charts, students’ perception of self-confidence concerning high-level thinking skills

Introducing Computational Thinking in K-12 Education: Historical, Epistemological, Pedagogical, Cognitive, and Affective Aspects

Introduction of scientific and cultural aspects of Computer Science (CS) (called "Computational Thinking" - CT) in K-12 education is fundamental. We focus on three crucial areas. 1. Historical, philosophical, and pedagogical aspects. What are the big ideas of CS we must teach? What are the historical and pedagogical contexts in which CT emerged, and why are relevant? What is the relationship between learning theories (e.g., constructivism) and teaching approaches (e.g., plugged and unplugged)? 2. Cognitive aspects. What is the sentiment of generalist teachers not trained to teach CS? What misconceptions do they hold about concepts like CT and "coding"? 3. Affective and motivational aspects. What is the impact of personal beliefs about intelligence (mindset) and about CS ability? What the role of teaching approaches? This research has been conducted both through historical and philosophical argumentation, and through quantitative and qualitative studies (both on nationwide samples and small significant ones), in particular through the lens of (often exaggerated) claims about transfer from CS to other skills. Four important claims are substantiated. 1. CS should be introduced in K-12 as a tool to understand and act in our digital world, and to use the power of computation for meaningful learning. CT is the conceptual sediment of that learning. We designed a curriculum proposal in this direction. 2. The expressions CT (useful to distantiate from digital literacy) and "coding" can cause misconceptions among teachers, who focus mainly on transfer to general thinking skills. Both disciplinary and pedagogical teacher training is hence needed. 3. Some plugged and unplugged teaching tools have intrinsic constructivist characteristics that can facilitate CS learning, as shown with proposed activities. 4. Growth mindset is not automatically fostered by CS, while not studying CS can foster fixed beliefs. Growth mindset can be fostered by creative computing, leveraging on its constructivist aspects

A Literature Review for the Implementation of Computational Thinking for Ontario K-12 Classrooms

The importance of the problem-solving skills involved in computational thinking has gained significant traction since its introduction. As Ontario seeks to implement coding into the school curriculum, an analysis of previous implementation of computational thinking could provide a framework for which to formulate new curriculum in the province. A literature review was completed to investigate the following three questions: (1) How has computational thinking been implemented into education in a K-12 environment? (2) What barriers will affect the implementation of computational thinking in a K-12 environment? (3) What grade levels are appropriate for implementing the varying competencies of computational thinking? This literature review sheds light on the need for teacher support, the political implications involved in introducing new curriculum, and where computational thinking best fits into current K-12 curriculum

Knowledge Level and Self-Confidence on The Computational Thinking Skills Among Science Teacher Candidates

The trending topic in today's education is computational thinking skills which are used to help to solve complicated problems easier. This study aims to identify the level of knowledge and self-confidence of science teacher candidates (physics and biology) on computational thinking skills. The survey research design was used through a mixed-method approach by combining quantitative and qualitative approaches. The quantitative study involved 1016 randomly selected groups of science teachers while in the qualitative study, eight science teachers were chosen based on the scores obtained from the quantitative study. The questionnaire was used as a quantitative data collecting technique to analyze descriptive statistics. Then, an interview was used as the qualitative data collecting technique and was analyzed through theme creation. The findings show that science teacher candidates have a high level of knowledge and self-confidence. The implication of this study is very important for teacher candidates because computational thinking can help to facilitate problems solving in everyday life. Teacher candidates need to be given knowledge and understanding of computational thinking skills, to have readiness and self-confidence in facing the challenges of the learning in the 21st-centur

Digital Competence and Computational Thinking of Student Teachers

Digital competence is one of the most demanded skills, and includes, among other aspects, the use of technological, informational, multimedia or communication skills and knowledge. In recent years, different institutions have included computational thinking among the different areas that make up this digital competence. However, there are few publications that deepen the relationship between computational thinking and digital competence. The present study analyzes the level of digital competence and computa-tional thinking of 248 Spanish university students, exploring the relation-ships between both abilities and the existing differences. According to the results, the majority of the students perceive themselves with a medium to a high level of digital competence, highlighting the multimedia and commu-nicative dimensions, as opposed to the more technological aspects. On the other hand, there is a correlation between computational thinking and digi-tal competence, especially with the communicative and technological areas. Likewise, the results indicate that women obtain lower results in their computational thinking and are perceived to be digitally less competent than men, especially in regard to the technological dimension. These results provide relevant information in terms of research and open the door to the development of training actions in student teachers to overcome the still-existing gender gaps

Programming unplugged : insights from theoretical models and teacher experiences.

Unplugged approaches to teaching Computational Thinking (CT), which are based on activities that do not require the use of a digital device or programming, are widely used in computing education. Evidence from the literature and practice indicates that this approach can be used successfully, although views on the value of Unplugged computing have been varied. Recently it was found that rather than comparing Unplugged with other approaches, combining Unplugged with teaching programming enabled students to achieve the same level of programming competence, but with higher self-efficacy, and a larger vocabulary in the programming language compared to a similar time span spent on programming alone. Despite this improved understanding of how to use Unplugged activities, there is little understanding of why they are effective and what ways they can be combined with plugged-in exercises effectively in a programming classroom and for teachers’ professional development (PD). In this thesis we use practical observations viewed through the lenses of theories of learning to understand why the Unplugged approach is effective. Computational Thinking in school curricula is about teaching students to understand how to use computation to solve problems, to create, and to discover new questions that can fruitfully be explored in other disciplines and professions as well as Computer Science. Teachers need to be able to effectively communicate the ideas of Computational Thinking to students and apply these within the context of their classroom. Our initial studies with teachers indicated that understanding the nature of the commonly identi- fied difficulties and confusion caused by computer jargon among teachers is important for finding ways for effective classroom delivery. We found that the concerns from teach- ers finding computer jargon difficult can be because the computational context in which they are applied makes them difficult for teachers to understand, rather than not knowing their meanings in the first place, and appropriate support can enable teachers to learn the techniques and skills that the terminology refers to. Using Unplugged material in teachers’ professional development, we tried to understand how they perceive the utility of Unplugged, particularly in introductory programming and understanding the jargon. Findings indicate that alternating Unplugged content in introductory programming does not hinder the teachers’ teaching efficacy and self-efficacy towards computer programming, yet teachers can be equipped with more content within the same time frame as a conventional teaching approach. Another lens that we use to understand how Unplugged and programming relate is the Notional Machine (NM), an abstract model of a computer created by teachers to facilitate learners’ understanding. It represents something they can (mentally) interact with to draw learners’ attention to hidden aspects of computing, is implicit in all programming teaching methods, and is a key to successful programming. We explore how Unplugged activities seem to have a close connection with Notional Machine, and therefore use the lens of Notional Machine to understand the relationship between Un- plugged and programming. Reviewing the existing Unplugged activities through this lens, we can understand where Unplugged has been successful in teaching programming and why. We also identify the possible gaps in Unplugged activities that need addressing for it to be further successful as a programming education tool. Accordingly, in our professional development experimental studies we developed and trialled new Unplugged activities focusing on modeling basic programming concepts, and studied their usefulness in alternating with conventional programming teaching practices. The usefulness of Unplugged activities in introductory programming was then considered through the lens of Semantic Waves, a concept that describes an ideal learning journey of a novice learner over a course of learning while shifting between expert and novice understanding, abstract and concrete context, and technical and simple meanings. Studying the behavior of the Semantic Waves of Unplugged activities we saw how, heuristically, the Zone of Proximal Development (ZPD) can be seen as a differentiation of a semantic profile of an Unplugged activity, essentially shifting learners back and forth between existing and new knowledge, while learning a programming concept. The Semantic Waves of Unplugged activities used to model programming concepts were analysed and compared with a plugged-in only lessons that taught the same concepts to show how alternating Unplugged activities with plugged-in experience successfully covers a wider semantic range, indicating the possibility of avoiding both learner anxiety as well as boredom, and enabling teachers to find better teaching strategies that suit their classrooms. Semantic profiles show the balance between what learners know and what they should know about what is actually happening, and the use of Unplugged activities supports the flow needed for creating effective semantic profiles, particularly in programming classrooms

Fostering Program Comprehension in Novice Programmers - Learning Activities and Learning Trajectories

This working group asserts that Program Comprehension (ProgComp) plays a critical part in the process of writing programs. For example, this paper is written from a basic draft that was edited and revised until it clearly presented our idea. Similarly, a program is written incrementally, with each step tested, debugged and extended until the program achieves its goal. Novice programmers should develop program comprehension skills as they learn to code so that they are able both to read and reason about code created by others, and to reflect on their code when writing, debugging or extending it. To foster such competencies our group identified two main goals: (g1) to collect and define learning activities that explicitly address key components of program comprehension and (g2) to define tentative theoretical learning trajectories that will guide teachers as they select and sequence those learning activities in their CS0/CS1/CS2 or K-12 courses. The WG has completed the first goal and laid down a strong foundation towards the second goal as presented in this report. After a thorough literature review, a detailed description of the Block Model is provided, as this model has been used with a dual purpose, to classify and present an extensive list of ProgComp tasks, and to describe a possible learning trajectory for a complex task, covering different cells of the Block Model matrix. The latter is intended to help instructors to decompose complex tasks and identify which aspects of ProgComp are being fostered

The Design and Evaluation of an Educational Software Development Process for First Year Computing Undergraduates

First year, undergraduate computing students experience a series of well-known challenges when learning how to design and develop software solutions. These challenges, which include a failure to engage effectively with planning solutions prior to implementation ultimately impact upon the students’ competency and their retention beyond the first year of their studies. In the software industry, software development processes systematically guide the development of software solutions through iterations of analysis, design, implementation and testing. Industry-standard processes are, however, unsuitable for novice programmers as they require prior programming knowledge. This study investigates how a researcher-designed educational software development process could be created for novice undergraduate learners, and the impact of this process on their competence in learning how to develop software solutions. Based on an Action Research methodology that ran over three cycles, this research demonstrates how an educational software development methodology (termed FRESH) and its operationalised process (termed CADET which is a concrete implementation of the FRESH methodology), was designed and implemented as an educational tool for enhancing student engagement and competency in software development. Through CADET, students were reframed as software developers who understand the value in planning and developing software solutions, and not as programmers who prematurely try to implement solutions. While there remain opportunities to further enhance the technical sophistication of the process as it is implemented in practice, CADET enabled the software development steps of analysis and design to be explicit elements of developing software solutions, rather than their more typically implicit inclusion in introductory CS courses. The research contributes to the field of computing education by exploring the possibilities of – and by concretely generating – an appropriate scaffolded methodology and process; by illustrating the use of computational thinking and threshold concepts in software development; and by providing a novel evaluation framework (termed AKM-SOLO) to aid in the continuous improvement of educational processes and courses by measuring student learning experiences and competencies