Exploring student information problem solving behaviour using fine-grained concept map and search tool data

Whitelock‐Wainwright, Alexander; Laan, Nathan; Wen, Dunwei; Gašević, Dragan

doi:10.1016/j.compedu.2019.103731

Cited by 40 publications

(24 citation statements)

References 59 publications

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“…We are accustomed to refer to the Genetic Algorithm as the traditional GA, which is the process described in figure 1 [13]. Its main steps can be described as follows:…”

Section: Basic Principlesmentioning

confidence: 99%

[Retracted] Construction of Student Information Management System Based on Data Mining and Clustering Algorithm

Yin

2021

Complexity

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Data mining is a new technology developed in recent years. Through data mining, people can discover the valuable and potential knowledge hidden behind the data and provide strong support for scientifically making various business decisions. This paper applies data mining technology to the college student information management system, mines student evaluation information data, uses data mining technology to design student evaluation information modules, and digs out the factors that affect student development and the various relationships between these factors. Predictive assessment of knowledge and personalized teaching decision-making provide the basis. First, the general situation of genetic algorithm and fuzzy genetic algorithm is introduced, and then, an improved genetic fuzzy clustering algorithm is proposed. Compared with traditional clustering algorithm and improved genetic fuzzy clustering algorithm, the effectiveness of the algorithm proposed in this paper is proved. Based on the analysis system development related tools and methods, in response to the needs of the student information management system, a simple student information management system is designed and implemented, which provides a platform and data source for the next application of clustering algorithm for performance analysis. Finally, clustering the students’ scores with a clustering algorithm based on fuzzy genetic algorithm, the experimental results show that this method can better analyze the students’ scores and help relevant teachers and departments make decisions.

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“…We are accustomed to refer to the Genetic Algorithm as the traditional GA, which is the process described in figure 1 [13]. Its main steps can be described as follows:…”

Section: Basic Principlesmentioning

confidence: 99%

[Retracted] Construction of Student Information Management System Based on Data Mining and Clustering Algorithm

Yin

2021

Complexity

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“…Concept map learning is thought to be a more effective learning strategy at all the levels of study (Lestari et al, 2019;Whitelock-Wainwright, Laan, Wen & Gasevic, 2020). The traditional learning strategy is useful strategy when there are a large number of learners in the presence of the instructor (Sanaie, Vasli, Sedighi & Sadeghi, 2019).…”

Section: Discussionmentioning

confidence: 99%

Assessment of academic achievements and memorisation power of students by concept map strategy and traditional lecture approach

Hafeez

2021

IJLT

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The challenges in the 21st century have made learning a complex process. In this age, new and conceptual learning strategies are being used to compete with the challenges. The concept map learning strategy has shown positive influences on students’ academic achievements and quality of education. This learning strategy has also showed a significant effect on students’ critical thinking skills. A research study has been conducted to assess the students’ academic achievements and memorisation power by concept map learning strategy and traditional learning approach. The students of a primary school studying in fifth grade in general course for section A (concept map learning strategy) and section B (Traditional lecture learning strategy) were assessed. The descriptive statistics and t-test analysis were also carried out on the results obtained from the students by concept map and traditional learning strategies. Statistical analysis showed that concept map learning strategy improved the students’ academic achievements and memorisation power significantly. Keywords: Critical thinking skills, learning skills, microbiology, strategies, primary school.

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“…: goal setting, acquiring information, monitoring the solution process, source evaluation, contrast or integrate information, and navigate-less efficiently. For example, concept maps were shown to ease the cognitive load of navigating through digital information, promote the understanding and the recall of text contents (V€ or€ os et al, 2011;Whitelock-Wainwright et al, 2020).However, typically, there are no external supports to overcome cognitive difficulties related to DPS processes. Therefore, we formulate the following three hypotheses.…”

Section: Theoretical Background and Hypothesesmentioning

confidence: 99%

“…Digital problems generally represent complex information problems because most of them solicit not only a mere sequence of routinized actions but more complex cognitive and metacognitive operations, such as handling a large quantity of information, using strategies to go through sub-goals, and monitoring the sub-processes may all be needed to come to a solution (Azevedo et al., 2010; Fischer & Funke, 2011; Greiff, Wüstenberg, et al., 2014; Lazonder & Rouet, 2008; OECD, 2009; Whitelock-Wainwright et al., 2020; Winne, 2011). Handling a large quantity of information may include the acquiring, evaluation and integration of sometimes contradictory information from different sources, locations and presentation forms (e.g., Rouet et al., 2017).…”

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confidence: 99%

Task Characteristics as Source of Difficulty and Moderators of the Effect of Time-on-Task in Digital Problem-Solving

Vörös

Kehl

Rouet

2020

Journal of Educational Computing Research

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To be able to solve complex information problems in a digital environment is a key 21st century skill. Technology users usually expect to achieve their goals in a fast and accurate way. However, the actual relationship between time-on-task and task outcome is currently not well understood. We analyzed data from a large-scale international study in which representative samples of adults had to solve more or less complex problems using standard computer applications. Our results indicate that different task characteristics influence the relationship between problem-solving performance and time-on-task in specific ways. Spending more time on a task is more likely to compensate an average problem solver when task complexity can be attributed to intrinsic task and technology drivers than when complexity stems from the cognitive/metacognitive activities belonging to information problem-solving processes per se, especially acquiring and evaluating information. Thus, the interpretation of time-on-task should take the source of difficulty into consideration. Implications for personal and professional development are discussed.

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Exploring student information problem solving behaviour using fine-grained concept map and search tool data

Cited by 40 publications

References 59 publications

[Retracted] Construction of Student Information Management System Based on Data Mining and Clustering Algorithm

[Retracted] Construction of Student Information Management System Based on Data Mining and Clustering Algorithm

Assessment of academic achievements and memorisation power of students by concept map strategy and traditional lecture approach

Task Characteristics as Source of Difficulty and Moderators of the Effect of Time-on-Task in Digital Problem-Solving

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