scholarly journals The Impact of Guided Metacognitive Feedback on Novice Programmers Using Learning by Teaching Environment

2019 ◽  
Vol 8 (2) ◽  
pp. 13-31
Author(s):  
Ahoud Alhazmi, Rafika Maaroufi Ahoud Alhazmi, Rafika Maaroufi
Keyword(s):  
Problem Solving ◽  
Programming Problem ◽  
Virtual Agents ◽  
Computer Based Learning ◽  
Learning By Teaching ◽  
Computer Based ◽  
Teaching Paradigm ◽  
Teachable Agent ◽  
Knowledge Of Correct Response ◽  
The Impact

Learning-by-teaching is a powerful approach that enhances students to think deeply, orally and repeatedly. Several computer-based systems have been implemented where students play the teacher role and virtual agents play the tutee role. The existing systems focus on various domains, but none of them has considered programming problem solving. Additionally, the majority of these systems did not provide metacognitive support. They only focus on providing feedback as correct answers, and this type of feedback is called knowledge of correct response. However, this paper explores the influence of guided metacognitive feedback on novice programmers in a teachable agent environment. For that, a computer-based learning environment is built to enable the novice programmers to teach programming problem solving to an animated agent. It combines learning-by-teaching technique and metacognitive support in order to assist those beginners to acquire comprehensive learning on how to solve unfamiliar problems and prepare those programmers for future learning tasks. We conduct an experiment to compare the effect of the aforementioned feedbacks on the novice programmers’ performance in learning-byteaching paradigm. The results show that the metacognitive feedback has positive effect on novice programmers’ achievement of solving problems. In addition, providing metacognitive feedback as explicit feedback in learning-by-teaching paradigm improves the novices' abilities to estimate what they know and what they do not know about how to solve new programming problems.

Estimating student ability and problem difficulty using item response theory (IRT) and TrueSkill

2019 ◽  
Vol 47 (2) ◽  
pp. 67-75 ◽  
Author(s):  
Youngjin Lee
Keyword(s):  
Data Mining ◽  
Item Response Theory ◽  
Problem Solving ◽  
Learning Environment ◽  
Item Response ◽  
Predictive Power ◽  
Response Theory ◽  
Content Type ◽  
Computer Based Learning ◽  
Computer Based

Purpose The purpose of this paper is to investigate an efficient means of estimating the ability of students solving problems in the computer-based learning environment. Design/methodology/approach Item response theory (IRT) and TrueSkill were applied to simulated and real problem solving data to estimate the ability of students solving homework problems in the massive open online course (MOOC). Based on the estimated ability, data mining models predicting whether students can correctly solve homework and quiz problems in the MOOC were developed. The predictive power of IRT- and TrueSkill-based data mining models was compared in terms of Area Under the receiver operating characteristic Curve. Findings The correlation between students’ ability estimated from IRT and TrueSkill was strong. In addition, IRT- and TrueSkill-based data mining models showed a comparable predictive power when the data included a large number of students. While IRT failed to estimate students’ ability and could not predict their problem solving performance when the data included a small number of students, TrueSkill did not experience such problems. Originality/value Estimating students’ ability is critical to determine the most appropriate time for providing instructional scaffolding in the computer-based learning environment. The findings of this study suggest that TrueSkill can be an efficient means for estimating the ability of students solving problems in the computer-based learning environment regardless of the number of students.

The Role of Self-Regulated Learning in Enhancing Conceptual Understanding of Rate of Chemical Reactions

2010 ◽  
pp. 248-267
Author(s):  
Eunice Eyitayo Olakanmi ◽  
Canan Blake ◽  
Eileen Scanlon
Keyword(s):  
Academic Performance ◽  
Chemical Reactions ◽  
Simulation Environment ◽  
Self Regulated Learning ◽  
Computer Based Learning ◽  
Starting Point ◽  
Regulated Learning ◽  
Computer Based ◽  
The Impact

The authors have investigated the effects of self-regulated learning (SRL) prompts on the academic performance of 30 year 9 students (12-13 year olds) learning science in a computer-based simulation environment by randomly assigning participants to either a SRL prompted or non-SRL prompted group. Mixed methods approaches were adopted for data collection and data analysis. Students in the SRL prompted group were given activity sheets which contained SRL prompts, whereas students in the non-SRL prompted group received no SRL-prompts in their activity sheets but some general prompts regarding how to follow the activity sheet. The incorporation of SRL prompted instructions into a computer-based simulation environment that teaches the rates of chemical reactions facilitated the shift in learners’ academic performance more than the non-SRL-prompted condition did. This shift was associated with the presence of the SRL behavioural prompts in the activity sheets. This study is a starting point in understanding the impact of the application of SRL-prompted instructions to the teaching of topics in a computer-based learning environment with a view to improving students’ academic attainment.

Modeling students’ problem solving performance in the computer-based mathematics learning environment

2017 ◽  
Vol 34 (5) ◽  
pp. 385-395 ◽  
Author(s):  
Young-Jin Lee
Keyword(s):  
Logistic Regression ◽  
Problem Solving ◽  
Learning Environment ◽  
Student Learning ◽  
Mathematics Learning ◽  
Quantitative Model ◽  
Content Type ◽  
Computer Based Learning ◽  
Instructional Scaffolding ◽  
Computer Based

Purpose The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can solve a mathematics problem correctly based on how well they solved other problems in the past. The usefulness of the model was evaluated by comparing the predicted probability of correct problem solving to the actual problem solving performance on the data set that was not used in the model building process. Findings The regularized logistic regression model showed a better predictive power than the standard Bayesian Knowledge Tracing model, the most frequently used quantitative model of student learning in the Educational Data Mining research. Originality/value Providing instructional scaffolding is critical in order to facilitate student learning. However, most computer-based learning environments use heuristics or rely on the discretion of students when they determine whether instructional scaffolding needs be provided. The predictive model of problem solving performance of students can be used as a quantitative guideline that can help make a better decision on when to provide instructional supports and guidance in the computer-based learning environment, which can potentially maximize the learning outcome of students.

scholarly journals Peningkatan Kemampuan Memecahkan Masalah melalui Media Komputer dalam Pembelajaran Matematika pada Siswa SMKN 1 Ngawen

2016 ◽  
Vol 22 (4) ◽  
pp. 432
Author(s):  
Urip Haryanto
Keyword(s):  
Action Research ◽  
Problem Solving ◽  
Action Observation ◽  
Learning Activities ◽  
Font Size ◽  
Problem Identification ◽  
Computer Based Learning ◽  
Computer Based ◽  
Answering Questions ◽  
Planning Action

This study aims at improving the students’ problem solving ability of Mathematics through computer-based learning, particularly in the space figures competency at SMK Negeri 1 Ngawen Gunungkidul. This study is categorized as classroom action research. The subjects of the study were the grade XI OC students of SMK Negeri 1 Ngawen Gunung Kidul. The study consisted of repetitious cycles. Every cycle consisted of problem identification, planning, action, observation, and reflection. The results of the study showed that: (1) the application of computer-based learning could improve the students’ problem solving ability of Mathematics and affected positively on the students’ achievement. The improvement was resulted from the conducive learning atmosphere (2) the students were highly interested in computer-based learning. They were more enthusiastic because they were able to confirm the answers directly; (3) to deal with the texts’ low legibility due to the mismatch between the background and the font size, the narration orally explained by the researcher was employed (4) the application of quizzes could motivate the students. They get involved actively in answering questions. The learning activities were more varied.

Empirical Evidence on the Relative Efficiency of Worked Examples versus Problem-Solving Exercises in Accounting Principles Instruction

2005 ◽  
Vol 20 (1) ◽  
pp. 21-32 ◽  
Author(s):  
Abdel K. Halabi ◽  
Juhani E. Tuovinen ◽  
Alan A. Farley
Keyword(s):  
Problem Solving ◽  
Prior Knowledge ◽  
Test Performance ◽  
Relative Efficiency ◽  
Worked Examples ◽  
Computer Based Learning ◽  
Introductory Accounting ◽  
Study Results ◽  
Response Measures ◽  
Computer Based

This study tested the relative efficiency of teaching material presented in the worked examples form of instruction compared to problem-solving exercises. Tests were also conducted to determine if subjects' prior exposure to accounting instruction affects results. Teaching materials were developed in Computer-Based Learning (CBL) format for one introductory accounting topic completed by 93 subjects. Response measures included test performance, learning effort, and instructional efficiency consisting of the combined measured performance and learning effort. The study results indicate that worked examples were more efficient than problem-solving exercises for students with no prior knowledge of accounting, while being equally efficient for those with prior knowledge.

The Effectiveness of Design Interventions in Improving the Ability of Older People to Perform Computer-Based Work

1998 ◽  
Vol 42 (2) ◽  
pp. 148-151 ◽  
Author(s):  
Sara J. Czaja ◽  
Joseph Sharit ◽  
Sankaran Nair
Keyword(s):  
Older Adults ◽  
Problem Solving ◽  
Cognitive Abilities ◽  
Interface Design ◽  
Data Entry ◽  
Complex Problem ◽  
Age Related ◽  
Computer Based ◽  
Improved Performance ◽  
The Impact

The objective of the current research was to evaluate the impact of age on the performance of computer-based work in order to develop design interventions that enhance the ability of older adults to perform these tasks. Specifically, two computer tasks, data entry, and a complex problem solving were investigated. Participants ranged in age from 20–75 years. Overall, the results indicted age differences in performance of both tasks. The younger participants had higher levels of performance Further, the results indicated that age-related differences in component cognitive abilities were related to performance. These data were used to develop design interventions such as modifying the layout of screen information. This paper presents data from the intervention studies. Overall the findings indicate that the interventions improved performance for all participants. For example, there were fewer keystroke errors for the data entry task and problem solving time was reduced for the problem solving task. These data are discussed in terms of understanding the extent to which fundamental interface design interventions can benefit older adults.

scholarly journals Learning styles: individualizing computer-based learning environments

2011 ◽  
Vol 3 (2) ◽  
Author(s):  
Anne Groat ◽  
Tim Musson
Keyword(s):  
Learning Styles ◽  
Learning Environments ◽  
Individual Characteristics ◽  
Computer Based Learning ◽  
Software Packages ◽  
Computer Based ◽  
Learner Differences ◽  
The Impact ◽  
Computer Based Learning Environments

While the need to adapt teaching to the needs of a student is generally acknowledged (see Corno and Snow, 1986, for a wide review of the literature), little is known about the impact of individual learner-differences on the quality of learning attained within computer-based learning environments (CBLEs). What evidence there is appears to support the notion that individual differences have implications for the degree of success or failure experienced by students (Ford and Ford, 1992) and by trainee end-users of software packages (Bostrom et al, 1990). The problem is to identify the way in which specific individual characteristics of a student interact with particular features of a CBLE, and how the interaction affects the quality of the resultant learning. Teaching in a CBLE is likely to require a subset of teaching strategies different from that subset appropriate to more traditional environments, and the use of a machine may elicit different behaviours from those normally arising in a classroom context.DOI:10.1080/0968776950030206

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