Feedback in the Concept Map Based Intelligent Knowledge Assessment System

Lukašenko, Romans; Anohina-Naumeca, Alla; Viļķelis, Marks; Grundspeņķis, Jānis

doi:10.2478/v10143-010-0020-z

Cited by 11 publications

(11 citation statements)

References 4 publications

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“…Most directive automated guidance for concept mapping activities in prior research was more specific and corrective than the directive guidance used in this study. For instance, they often pointed out inaccurate connections (e.g., Person et al, ), highlighted discrepancies between student‐generated and expert maps (e.g., Lukasenko et al, ), and presented specific data on student performance, such as a number of accurate and inaccurate concepts, propositions, and relationships (e.g., Gouli et al, ). Compared to these studies, the directive automated guidance used in this study provided conceptual information without explicitly pointing out which connections were accurate or which icons should be modified.…”

Section: Discussionmentioning

confidence: 99%

“…Even with open‐ended activities, such as creating concept maps, many studies provide directive guidance that detects which concepts are inaccurate or that informs students what should be revised in their maps (e.g., Attali & Powers, ; Gouli, Gogoulou, & Grigoriadou, ). For example, several concept mapping tools provided directive guidance providing overall scores, describing a number of correct concepts compared to a given expert map, or highlighting discrepancies between student‐generated and expert maps (Conlon, ; Luckie, Harrison, & Ebert‐May, ; Lukasenko, Anohina‐Naumeca, Vilkelis, & Grundspenkis, ; Person et al, ). These studies report that directive guidance is effective in reducing the number of errors students made, helping students fix their mistakes, and encouraging them to revise their responses (Anderson et al, ; Attali & Powers, ; Boramy, ; Koedinger & Aleven, ; Koedinger, McLaughlin, & Heffernan, ).…”

Section: Rationalementioning

confidence: 99%

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Designing automated guidance for concept diagrams in inquiry instruction

Ryoo

Linn

2016

J Res Sci Teach

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Advances in automated scoring technologies have the potential to support student learning during inquiry instruction by providing timely and adaptive guidance on individual students' responses. To identify which forms of automated guidance can be beneficial for inquiry learning, we compared reflective guidance to directive guidance for student-generated concept diagrams in web-based inquiry instruction. Eleven intact classes were randomly assigned to either a reflective guidance or a directive guidance condition. After creating a concept diagram showing energy flow in life science during the inquiry instruction, the directive group was told specific ways to improve their diagram, while the reflective group was told to revisit a relevant visualization step to locate useful information. The results from the concept diagrams, as well as individual tests, show that both forms of automated guidance helped students add target energy concepts, but reflective guidance was significantly more effective than directive guidance in improving students' coherent understanding of how energy flows in life science. Analyses of log data revealed that the reflective group was more likely to revisit the visualization step as suggested in the guidance, which significantly enhanced student learning. Detailed analyses suggest that revisiting relevant materials to find useful information challenged students to identify gaps in their understanding and distinguish among multiple ideas. This study shows the value of designing reflective automated guidance for helping students engage in evidence-gathering practices and enhance their understanding of scientific concepts. The findings suggest promising directions for the design of automated adaptive guidance to support complex science learning. # 2016 Wiley Periodicals, Inc. J Res Sci Teach

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Section: Discussionmentioning

confidence: 99%

Section: Rationalementioning

confidence: 99%

Designing automated guidance for concept diagrams in inquiry instruction

Ryoo

Linn

2016

J Res Sci Teach

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“…Although adaptive and automated elements are increasingly common in online learning environments (e.g., Aleven et al, 2010;Lukasenko et al, 2010;Vandewaetere et al, 2011;Gerard et al, 2015Gerard et al, , 2016, they have typically been designed and implemented for a single learning activity in a specific domain. The reason for this is simple; even adaptive guidance for a single well-defined learning task generally requires years of research and development.…”

Section: Adaptive and Automated Scaffoldingmentioning

confidence: 99%

Automated Feedback Can Improve Hypothesis Quality

et al. 2019

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Stating a hypothesis is one of the central processes in inquiry learning, and often forms the starting point of the inquiry process. We designed, implemented, and evaluated an automated parsing and feedback system that informed students about the quality of hypotheses they had created in an online tool, the hypothesis scratchpad. In two pilot studies in different domains ("supply and demand" from economics and "electrical circuits" from physics) we determined the parser's accuracy by comparing its judgments with those of human experts. A satisfactory to high accuracy was reached. In the main study (in the "electrical circuits" domain), students were assigned to one of two conditions: no feedback (control) and automated feedback. We found that the subset of students in the experimental condition who asked for automated feedback on their hypotheses were much more likely to create a syntactically correct hypothesis than students in either condition who did not ask for feedback.

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“…The system has twofold goals in the context of integration of technology into the traditional educational process [27]: a) to promote students' knowledge self-assessment, and b) to support teachers in improvement of study courses through systematic assessment and analysis of students' knowledge. Knowledge selfassessment is supported by the evaluation of students' concept maps and provision of informative and tutoring feedback.…”

Section: Overview Of Ikasmentioning

confidence: 99%

“…The usage scenario of IKAS [27] assumes that a teacher divides a course into several assessment stages. A stage can be any logically completed part of the course, for example, a chapter.…”

Section: Overview Of Ikasmentioning

confidence: 99%

Conception of the Animated Interface Agent for the Concept Map Based Intelligent Knowledge Assessment System

Anohina-Naumeca¹,

Lukašenko²,

Skripkins³

2011

Scientific Journal of Riga Technical University. Computer Sciences

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-The paper presents the conception of the animated interface agent for the concept map based assessment system. The agent is being developed with an aim to solve problems related to rare use or users' unawareness of functional capabilities of the system. The conception consists of agent's goal, functions, inputs, outputs, embodiment, and properties. It is based on the interface agent characteristics and design requirements summarized in the paper, as well as analysis of system needs.

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Feedback in the Concept Map Based Intelligent Knowledge Assessment System

Cited by 11 publications

References 4 publications

Designing automated guidance for concept diagrams in inquiry instruction

Designing automated guidance for concept diagrams in inquiry instruction

Automated Feedback Can Improve Hypothesis Quality

Conception of the Animated Interface Agent for the Concept Map Based Intelligent Knowledge Assessment System

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