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The effects of first programming language on college students' computing attitude and achievement: a comparison of graphical and textual languages

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COMPUTER SCIENCE EDUCATION 2019年第1期29卷 23-48页

作者： Chen, Chen Haduong, Paulina Brennan, Karen Sonnert, Gerhard Sadler, Philip Harvard Smithsonian Ctr Astrophys Sci Educ Dept 60 Garden St Cambridge MA 02138 USA Harvard Grad Sch Educ Cambridge MA USA

Background and Context: The relationship between novices' first programming language and their future achievement has drawn increasing interest owing to recent efforts to expand K-12 computing education. This article contributes to this topic by analyzing data from a retrospective study of more than 10,000 undergraduates enrolled in introductory computer science courses at 118 U.S. institutions of higher education. Objective: We explored the relationship between students' first programming languages and both their final grades in an introductory computer science course and their attitudes about programming. Method: Multiple matching techniques compared those whose first language was graphical (e.g., Scratch), textual (e.g., Java), or absent prior to college. Findings: Having any prior programming experience had positive effects on both attitudes about programming and grades in introductory computer science courses. Importantly, students whose first language was graphical had higher grades than did students whose first language was textual, when the languages were introduced in or before early adolescent years.

关键词： programming and programming languages first programming language pedagogical issues secondary education teaching and learning strategies postsecondary education

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A scoping review of computational thinking assessments in higher education

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JOURNAL OF COMPUTING IN HIGHER EDUCATION 2022年第2期34卷 416-461页

作者： Lu, Chang Macdonald, Rob Odell, Bryce Kokhan, Vasyl Epp, Carrie Demmans Cutumisu, Maria Univ Alberta Edmonton AB Canada

The field of computational thinking (CT) is developing rapidly, reflecting its importance in the global economy. However, most empirical studies have targeted CT in K-12, thus, little attention has been paid to CT in higher education. The present scoping review identifies and summarizes existing empirical studies on CT assessments in post-secondary education, aiming to reveal the current trends of empirical research in this domain and key features of recent CT assessment instruments. It examines 33 peer-reviewed journal articles published between 2013 and 2019 from six databases. Results show that most assessment tools are designed for computing science and engineering undergraduates or pre-service and in-service teachers in these subjects. Most tools involve in-class interventions to promote CT skills. Several assessment formats were adopted in the selected studies, including selected-response questions, constructed-response questions, Likert scales, interviews, programming artefacts, observations, and interviews. Finally, most assessment instruments attempt to measure skills from a combination of dimensions including CT Concepts, Practices, and Perspectives from a hybrid-competency framework. More specifically, the skills assessed in most studies are algorithmic thinking, problem solving, data, logic and logical thinking, and abstraction. Findings may help instructors to select CT assessments for higher education and researchers to focus on less explored research areas.

关键词： Computational thinking programming and programming languages Learning and assessment Higher education

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Using robot-based practices to develop an activity that incorporated the 6E model to improve elementary school students' learning performances

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INTERACTIVE LEARNING ENVIRONMENTS 2022年第1期30卷 85-99页

作者： Hsiao, Hsien-Sheng Lin, Yi-Wei Lin, Kuen-Yi Lin, Chien-Yu Chen, Jheng-Han Chen, Jyun-Chen Natl Taiwan Normal Univ Dept Technol Applicat & Human Resource Dev Taipei Taiwan Natl Taiwan Normal Univ Inst Res Excellence Learning Sci Taipei Taiwan Natl Taiwan Normal Univ Chinese Language & Technol Ctr Taipei Taiwan Natl Acad Educ Res Res Ctr Testing & Assessment New Taipei Taiwan Natl Appl Res Labs Sci & Technol Policy Res & Informat Ctr Taipei Taiwan

This study used robot-based practices to develop an activity that incorporated the 6E model. The sixth-grade students learned interdisciplinary knowledge about how to use Arduino electronic components, microcontrollers, and hands-on tools to make a "Crab Robot." In addition, the students learned how to use Scratch programming language to control the robot and complete the "Crab Robot Crossing the Road" task. The study implemented a quasi-experimental design to examine whether the students who learned the robot-based activity using the 6E model acquired better learning motivation, learning performance, computational thinking ability, and hands-on ability than those who learned the activity through lectures. This study adopted purposive sampling to select 70 sixth-grade students from four classes, which were divided into the experimental group (6E model) and the control group (lectures). The experiment was conducted over a period of 18 weeks (for a total duration of 1,440 minutes). The results from the pretests-posttests showed that both groups of students improved their learning motivation, learning performance, computational thinking ability, and hands-on ability;however, the experimental group's scores were significantly better. More importantly, this study provides a pedagogy manuscript for instructors who want to teach mechatronics programs and programming design education.

关键词： Robot-based practices interdisciplinary projects programming and programming languages computational thinking ability hands-on ability

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Transitioning from introductory block-based and text-based environments to professional programming languages in high school computer science classrooms

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COMPUTERS & EDUCATION 2019年 142卷 103646-000页

作者： Weintrop, David Wilensky, Uri Univ Maryland Coll Educ Coll Informat Studies College Pk MD 20742 USA Northwestern Univ Ctr Connected Learning & Comp Based Modeling Evanston IL 60208 USA

Block-based programming languages are becoming increasingly common in introductory computer science classrooms across the K-12 spectrum. One justification for the use of block-based environments in formal educational settings is the idea that the concepts and practices developed using these introductory tools will prepare learners for future computer science learning opportunities. This view is built on the assumption that the attitudinal and conceptual learning gains made while working in the introductory block-based environments will transfer to conventional text-based programming languages. To test this hypothesis, this paper presents the results of a quasi-experimental classroom study in which programming novices spent five-week using either a block-based or text-based programming environment. After five weeks in the introductory tool, students transitioned to Java, a conventional text-based programming language. The study followed students for 10 weeks after the transition. Over the course of the 15-week study, attitudinal and conceptual assessments were administered and student-authored programs were collected. Conceptual learning, attitudinal shifts, and changes in programming practices were analyzed to evaluate how introductory modality impacted learners as they transitioned to a professional, text-based programming language. The findings from this study build on earlier work that found a difference in performance on content assessments after the introductory portion of the study (Weintrop & Wilensky, 2017a). This paper shows the difference in conceptual learning that emerged after five weeks between the block-based and text-based conditions fades after 10 weeks in Java. No differences in programming practices were found between the two conditions while working in Java. Likewise, differences in attitudinal measures that emerged after working in the introductory environments also faded after 10 weeks in Java, resulting in no difference between the conditions

关键词： Evaluation of CAL systems Interactive learning environments programming and programming languages Secondary education Teaching/leaming strategies

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Scaffolding problem solving with learners' own self explanations of subgoals

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JOURNAL OF COMPUTING IN HIGHER EDUCATION 2021年第2期33卷 499-523页

作者： Margulieux, Lauren E. Catrambone, Richard Georgia State Univ Dept Learning Sci Atlanta GA 30302 USA Georgia Inst Technol Sch Psychol Atlanta GA 30332 USA

Procedural problem solving is an important skill in most technical domains, like programming, but many students reach problem solving impasses and flounder. In most formal learning environments, instructors help students to overcome problem solving impasses by scaffolding initial problem solving. Relying on this type of personalized interaction, however, limits the scale of formal instruction in technical domains, or it limits the efficacy of learning environments without it, like many scalable online learning environments. The present experimental study explored whether learners' self-explanations of worked examples could be used to provide personalized but non-adaptive scaffolding during initial problem solving to improve later performance. Participants who received their own self-explanations as scaffolding for practice problems performed better on a later problem-solving test than participants who did not receive scaffolding or who received expert's explanations as scaffolding. These instructional materials were not adaptive, making them easy to distribute at scale, but the use of the learner's own explanations as scaffolding made them effective.

关键词： Scaffolding Problem solving Distance education and telelearning Post-secondary education programming and programming languages Teaching learning strategies

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Unplugged or plugged-in programming learning: A comparative experimental study

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COMPUTERS & EDUCATION 2022年 184卷 104505-104505页

作者： Sigayret, Kevin Tricot, Andre Blanc, Nathalie Univ Paul Valery Montpellier 3 Lab Epsylon EA 4556 Rue Prof Henri Serre F-34000 Montpellier France

In recent years, computer programming has reappeared in school curricula with the aim of transmitting knowledge and skills beyond the simple ability to code. However, there are different ways of teaching this subject and very few experimental studies compare plugged-in and unplugged programming learning. The purpose of this study is to highlight the impact of plugged-in or unplugged learning on students' performance and subjective experience. To this end, we designed an experimental study with 217 primary school students divided into two groups and we measured their knowledge of computational concepts, ability to solve algorithmic problem, motivation toward the instruction, self-belief and attitude toward science. The programming sessions were designed to be similar between the two conditions, only the tools were different. Computers and Scratch software were used in the plugged-in group while the unplugged group used paper instructions, pictures, figurines and body movements instead. The results show better learning performance in the plugged-in group. Furthermore, although motivation dropped slightly in both groups, this drop was only significant in the unplugged condition. Gender also seems to be an important factor, as girls exhibit a lower post-test motivation and a lower willingness to pursue their practice in programming outside the school context. However, this effect on motivation was only observable in the plugged-in group which suggests that educational programming software may have a positive but gendered motivational impact.

关键词： Elementary education Improving classroom teaching programming and programming languages Teaching learning strategies

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An overview and comparison of supervised data mining techniques for student exam performance prediction

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COMPUTERS & EDUCATION 2020年 143卷 103676-103676页

作者： Tomasevic, Nikola Gvozdenovic, Nikola Vranes, Sanja Univ Belgrade Mihajlo Pupin Inst Volgina 15 Belgrade 11060 Serbia

Recent increase in the availability of learning data has given educational data mining an importance and momentum, in order to better understand and optimize the learning process and environments in which it occurs. The aim of this paper is to provide a comprehensive analysis and comparison of state of the art supervised machine learning techniques applied for solving the task of student exam performance prediction, i.e. discovering students at a "high risk" of dropping out from the course, and predicting their future achievements, such as for instance, the final exam scores. For both classification and regression tasks, the overall highest precision was obtained with artificial neural networks by feeding the student engagement data and past performance data, while the usage of demographic data did not show significant influence on the precision of predictions. To exploit the full potential of the student exam performance prediction, it was concluded that adequate data acquisition functionalities and the student interaction with the learning environment is a prerequisite to ensure sufficient amount of data for analysis.

关键词： Adult learning Evaluation methodologies Intelligent tutoring systems programming and programming languages

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International Journal of Child-Computer Interaction 2025年 44卷

作者： Chiara Montuori Lucia Ronconi Gabriele Pozzan Costanza Padova Tullio Vardanega Barbara Arfé Department of Developmental Psychology and Socialization University of Padua Italy Department of Mathematics University of Padua Italy Human Inspired Technologies Research Centre University of Padua Italy

Past research has shown that children as young as 4–6 years can learn to code through virtual (digital) or plugged (physical, analogic) coding activities, and that exposure to those activities benefits children's cognitive skills too. Indeed, two executive functions (EFs), planning and response inhibition, seem to be strongly associated with coding. However, it remains unclear whether children's cognitive response to virtual coding instruction varies with children's age. Only a few studies to date, mostly focused on older students (aged 10–18 years), have examined age-related differences in response to coding instruction. No such studies as yet have explored whether age differences in learning to code also translate in differential cognitive benefits of coding with children's age. The present study compared the response to an 8-h coding intervention of 273 first graders (5–7 years) and 164 fourth graders (8–10 years), examining whether their respective gains in coding abilities, planning (Tower of London test), and response inhibition (Stroop test and NEPSY-II square/circle test) differed following exposure to coding. Multilevel analyses with socio-economic status covariate show significant effects of the intervention on both 1st and 4th graders' coding skills and across all cognitive measures (planning accuracy, response inhibition accuracy and time). For coding accuracy, both first and fourth graders improved, with large effect sizes ( d = −1.53 for first graders, d = −1.84 for fourth graders). The experimental groups showed greater post-test gains in planning accuracy in both grades ( d = −1.44 for first graders, d = −0.91 for fourth graders). First graders decreased inhibition errors significantly after the intervention in both NEPSY-II and Stroop tasks (respectively, t(425) = 8.21, p < 0.001, d = 0.80; t(425) = 11.37, p < 0.001, d = 1.10), as well as the fourth graders (t(427) = 3.79, p < 0.001, d = 0.38 in NEPSY-II, t(427) = 4.56, p < 0.001, d = 0.

关键词： Primary education Improving classroom teaching Teaching/learning strategies programming and programming languages Executive functions

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Multiple-Choice Questions in programming Courses: Can We Use Them and Are Students Motivated by Them?

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ACM TRANSACTIONS ON COMPUTING EDUCATION 2019年第1期19卷 1–16页

作者： Abreu, Pedro Henriques Silva, Daniel Castro Gomes, Anabela Univ Coimbra Fac Sci & Technol Dept Informat Engn Ctr Informat & Syst Polo 2 P-3030290 Coimbra Portugal Univ Porto Fac Engn Dept Informat Engn Artificial Intelligence & Comp Sci Lab Rua Dr Roberto Frias S-N P-4200465 Porto Portugal Coimbra Inst Engn Dept Informat Engn & Syst Ctr Informat & Syst Rua Pedro Nunes P-3030199 Coimbra Portugal

Low performance of nontechnical engineering students in programming courses is a problem that remains unsolved. Over the years, many authors have tried to identify the multiple causes for that failure, but there is unanimity on the fact that motivation is a key factor for the acquisition of knowledge by students. To better understand motivation, a new evaluation strategy has been adopted in a second programming course of a nontechnical degree, consisting of 91 students. The goals of the study were to identify if those students felt more motivated to answer multiple-choice questions in comparison to development questions, and what type of question better allows for testing student knowledge acquisition. Possibilities around the motivational qualities of multiple-choice questions in programming courses will be discussed in light of the results. In conclusion, it seems clear that student performance varies according to the type of question. Our study points out that multiple-choice questions can be seen as a motivational factor for engineering students and it might also be a good way to test acquired programming concepts. Therefore, this type of question could be further explored in the evaluation points.

关键词： Student's motivation evaluation methodologies pedagogical issues programming and programming languages

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A Scoping Review of Empirical Research on Recent Computational Thinking Assessments

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JOURNAL OF SCIENCE EDUCATION AND TECHNOLOGY 2019年第6期28卷 651-676页

作者： Cutumisu, Maria Adams, Cathy Lu, Chang Univ Alberta Fac Educ 6-102 Educ Ctr North Edmonton AB T6G 2G5 Canada

Computational thinking (CT) is regarded as an essential twenty-first century competency and it is already embedded in K-12 curricula across the globe. However, research on assessing CT has lagged, with few assessments being implemented and validated. Moreover, there is a lack of systematic grouping of CT assessments. This scoping review examines 39 empirical studies published within the last five years, coded by the specific competencies outlined in existing CT frameworks, to identify and classify the key features of existing CT assessments. Results show that most studies target K-12 settings, focus on interventions that promote CT concepts and practices, adopt a quasi-experimental design, use selected-response items as the dominant testing form, and mainly assess algorithmic thinking, abstraction, problem decomposition, logical thinking, and data. Finally, few CT assessments have been validated in educational settings. Implications include identifying gaps in the CT assessment literature, deepening our understanding of the nature of CT, focusing on the validation of CT assessments, and guiding researchers and practitioners in choosing developmentally appropriate CT assessments. Cognitive and educational implications for future research inquiry include the development of new assessment tools that comprehensively assess CT and its relation to learning.

关键词： Computational thinking Computational literacy Coding K-12 education Learning and assessment programming and programming languages

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