Dishita Turakhia - Academia.edu (original) (raw)

Papers by Dishita Turakhia

arXiv (Cornell University), Oct 25, 2023

Figure 1: (a) Designers use Adapt2Learn's user interface to configure the adaptation of their ada... more Figure 1: (a) Designers use Adapt2Learn's user interface to configure the adaptation of their adaptive training tools, such as (b) an adaptive basketball stand that adapts its hoop height and width. Adapt2Learn auto-generates the learning algorithm as a micro-controller script that can be deployed to the tool. The algorithm uses sensor values to assess a learner's performance, computes the optimal training difficulty, and then varies the training difficulty by adapting the hoop height and width. (c) Adapt2Learn's built-in visualization tool lets designers visualize the tool's adaptation and evaluate the learning algorithm.

Figure 1: We investigate if adaptive learning tools that automatically adapt their shape to adjus... more Figure 1: We investigate if adaptive learning tools that automatically adapt their shape to adjust the task difficulty based on a learner's performance can help in motor-skill training. To this end, we built (a) a study prototype in the form of an adaptive basketball stand that can adjust its hoop size and basket height. Our studies show that when the tool adapts automatically, training leads to significantly higher learning gains in comparison to training with (b) a static tool and (c) a manually adaptive tool for which the learners choose the difficulty level themselves.

Designing Interactive Systems Conference, Jun 13, 2022

Figure 1: (a) Before buying sensors, makers can visualize sensor data from the datasheet to get a... more Figure 1: (a) Before buying sensors, makers can visualize sensor data from the datasheet to get a frst idea of what sensors can sense. (b) Before physically building the prototype, makers can visualize sensor data in AR to see what sensors can sense in the context in which the prototype will be used. (c) After assembling the physical prototype, makers can visualize live data either in the 3D editor or via AR to verify that the sensors work as expected and to make further changes as needed.

Figure 1: We present ReflectiveMaker-a toolkit for experts and educators to design refection exer... more Figure 1: We present ReflectiveMaker-a toolkit for experts and educators to design refection exercises for novice learners in makerspaces. Experts and educators can use ReflectiveMaker to design the refection prompts during fabrication activities, sense the user's activities, identify suitable events for prompting refection, record the user's refections, and analyze data on their learning progress.

Figure 1: Adaptive training tools adjust the task difculty according to the learner's current per... more Figure 1: Adaptive training tools adjust the task difculty according to the learner's current performance: (a) Adaptive basketball hoop that can be widened/tightened and raised/lowered. (b) Adaptive training wheels for a bike that can be raised/lowered. (c) Wobbleboard with infatable/defatable support cushion to increase/decrease stability. (d) An infatable/defatable golf arm band that increases/decreases restriction when bending the elbow.

Figure 1: To support learners of makerskills with reflection exercises during their activities, w... more Figure 1: To support learners of makerskills with reflection exercises during their activities, we propose using augmented reality (AR). In this work, we propose a framework to design reflective exercises in AR, and illustrate a system to use an AR head-mounted device (HMD) to monitor, prompt, and record reflections while the maker activity is in progress, and use AR affordances to directly point at the real-world objects for contextualization, overlay information related to the maker activities, and provide multimodal feedback to the learners for self-reflection exercises.

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Figure 1: To support learners of makerskills with reflection exercises during their activities, w... more Figure 1: To support learners of makerskills with reflection exercises during their activities, we propose using augmented reality (AR). In this work, we propose a framework to design reflective exercises in AR, and illustrate a system to use an AR head-mounted device (HMD) to monitor, prompt, and record reflections while the maker activity is in progress, and use AR affordances to directly point at the real-world objects for contextualization, overlay information related to the maker activities, and provide multimodal feedback to the learners for self-reflection exercises.

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Figure 1: We present an interview study investigating seven educators' experiences of teaching ma... more Figure 1: We present an interview study investigating seven educators' experiences of teaching maker skills across five makerspaces. Our thematic analysis of the educators' practices resulted in an outline of the competencies that the educators centralize in their teaching, and the strategies they integrate to teach the competencies. (Thicker lines represent a stronger connection and dotted lines represent weaker connection)

The Adjunct Publication of the 35th Annual ACM Symposium on User Interface Software and Technology

Figure 1: We present ReflectiveMaker-a toolkit for experts and educators to design refection exer... more Figure 1: We present ReflectiveMaker-a toolkit for experts and educators to design refection exercises for novice learners in makerspaces. Experts and educators can use ReflectiveMaker to design the refection prompts during fabrication activities, sense the user's activities, identify suitable events for prompting refection, record the user's refections, and analyze data on their learning progress.

Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2017.Thesis: S.M... more Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2017.Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 97-99).The vision of this research is to propose a novel computational framework to study Creative Thinking. If we are to embed machines with creative thinking abilities, then we first need to study the evanescent nature of human creative thinking. Creative thinking is neither entirely random nor strictly logical, making it difficult to t its computation into structured logical models of thinking. Given this conundrum, how can we computationally study the process of thinking creatively? In this research, I first present the current scientific de...

CHI Conference on Human Factors in Computing Systems Extended Abstracts, Apr 27, 2022

The Adjunct Publication of the 35th Annual ACM Symposium on User Interface Software and Technology

Figure 1: My research lies at the intersection of system design, learning sciences, and technolog... more Figure 1: My research lies at the intersection of system design, learning sciences, and technologies that support learning of physical skills. In particular, I have worked on three sets of projects-(1) adaptive learning of motor skills, (2) game-based learning for fabrication skills, and (3) refection-based learning of maker skills.

CHI Conference on Human Factors in Computing Systems

Designing Interactive Systems Conference

Figure 1: (a) Before buying sensors, makers can visualize sensor data from the datasheet to get a... more Figure 1: (a) Before buying sensors, makers can visualize sensor data from the datasheet to get a frst idea of what sensors can sense. (b) Before physically building the prototype, makers can visualize sensor data in AR to see what sensors can sense in the context in which the prototype will be used. (c) After assembling the physical prototype, makers can visualize live data either in the 3D editor or via AR to verify that the sensors work as expected and to make further changes as needed.

The vision of this research is to propose a novel computational framework to study Creative Think... more The vision of this research is to propose a novel computational framework to study Creative Thinking. If we are to embed machines with creative thinking abilities, then we first need to study the evanescent nature of human creative thinking. Creative thinking is neither entirely random nor strictly logical, making it difficult to fit its computation into structured logical models of thinking. Given this conundrum, how can we computationally study the process of thinking creatively? In this research, I first present the current scientific definitions of creative thinking. Through literary survey of cognitive, computational and design thinking frameworks, I identify the missing links between human creativity and AI models of creative thinking. I assert that creative thinking is result of two features of human intelligence, cognitive diversity and social interaction. Cognitive diversity or the ability to parse knowledge in different ways is a crucial aspect of creative thinking. Furthe...

Creativity and Cognition, 2021

The primary objective of the research is to study the non-linear behavior of irregular tensegrity... more The primary objective of the research is to study the non-linear behavior of irregular tensegrity structures and formulate a computational generative, evaluative and algorithmic method to design a structurally dynamic tensegrity system, with inherent potential to adapt to the varying contexts and its respective demands, requirements and spatial needs.

Many motor skills that people learn throughout their lives involve mastering a physical tool, suc... more Many motor skills that people learn throughout their lives involve mastering a physical tool, such as riding a bike, writing with a pen, or playing basketball. To reduce the level of difficulty, learners use physical learning aids, such as training wheels for a bike, that provide physical support. To date, these learning aids only come in predefined levels: For instance, training wheels are either mounted or taken off. This jump from beginner to expert level makes the transition difficult for learners. In this paper, we address this challenge by adapting the physical tool according to the learner’s progress. For instance, while learning to ride a bike, we monitor learners’ balancing skills and as they improve, we gradually lift the training wheels to reduce support and increase the difficulty. Thus, our approach enables a step-by-step transition from beginner to expert level that, similar to existing adaptive learning systems for math and language skills, is personalized for each in...

arXiv (Cornell University), Oct 25, 2023

Figure 1: (a) Designers use Adapt2Learn's user interface to configure the adaptation of their ada... more Figure 1: (a) Designers use Adapt2Learn's user interface to configure the adaptation of their adaptive training tools, such as (b) an adaptive basketball stand that adapts its hoop height and width. Adapt2Learn auto-generates the learning algorithm as a micro-controller script that can be deployed to the tool. The algorithm uses sensor values to assess a learner's performance, computes the optimal training difficulty, and then varies the training difficulty by adapting the hoop height and width. (c) Adapt2Learn's built-in visualization tool lets designers visualize the tool's adaptation and evaluate the learning algorithm.

Figure 1: We investigate if adaptive learning tools that automatically adapt their shape to adjus... more Figure 1: We investigate if adaptive learning tools that automatically adapt their shape to adjust the task difficulty based on a learner's performance can help in motor-skill training. To this end, we built (a) a study prototype in the form of an adaptive basketball stand that can adjust its hoop size and basket height. Our studies show that when the tool adapts automatically, training leads to significantly higher learning gains in comparison to training with (b) a static tool and (c) a manually adaptive tool for which the learners choose the difficulty level themselves.

Designing Interactive Systems Conference, Jun 13, 2022

Figure 1: (a) Before buying sensors, makers can visualize sensor data from the datasheet to get a... more Figure 1: (a) Before buying sensors, makers can visualize sensor data from the datasheet to get a frst idea of what sensors can sense. (b) Before physically building the prototype, makers can visualize sensor data in AR to see what sensors can sense in the context in which the prototype will be used. (c) After assembling the physical prototype, makers can visualize live data either in the 3D editor or via AR to verify that the sensors work as expected and to make further changes as needed.

Figure 1: We present ReflectiveMaker-a toolkit for experts and educators to design refection exer... more Figure 1: We present ReflectiveMaker-a toolkit for experts and educators to design refection exercises for novice learners in makerspaces. Experts and educators can use ReflectiveMaker to design the refection prompts during fabrication activities, sense the user's activities, identify suitable events for prompting refection, record the user's refections, and analyze data on their learning progress.

Figure 1: Adaptive training tools adjust the task difculty according to the learner's current per... more Figure 1: Adaptive training tools adjust the task difculty according to the learner's current performance: (a) Adaptive basketball hoop that can be widened/tightened and raised/lowered. (b) Adaptive training wheels for a bike that can be raised/lowered. (c) Wobbleboard with infatable/defatable support cushion to increase/decrease stability. (d) An infatable/defatable golf arm band that increases/decreases restriction when bending the elbow.

Figure 1: To support learners of makerskills with reflection exercises during their activities, w... more Figure 1: To support learners of makerskills with reflection exercises during their activities, we propose using augmented reality (AR). In this work, we propose a framework to design reflective exercises in AR, and illustrate a system to use an AR head-mounted device (HMD) to monitor, prompt, and record reflections while the maker activity is in progress, and use AR affordances to directly point at the real-world objects for contextualization, overlay information related to the maker activities, and provide multimodal feedback to the learners for self-reflection exercises.

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Figure 1: To support learners of makerskills with reflection exercises during their activities, w... more Figure 1: To support learners of makerskills with reflection exercises during their activities, we propose using augmented reality (AR). In this work, we propose a framework to design reflective exercises in AR, and illustrate a system to use an AR head-mounted device (HMD) to monitor, prompt, and record reflections while the maker activity is in progress, and use AR affordances to directly point at the real-world objects for contextualization, overlay information related to the maker activities, and provide multimodal feedback to the learners for self-reflection exercises.

Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems

Figure 1: We present an interview study investigating seven educators' experiences of teaching ma... more Figure 1: We present an interview study investigating seven educators' experiences of teaching maker skills across five makerspaces. Our thematic analysis of the educators' practices resulted in an outline of the competencies that the educators centralize in their teaching, and the strategies they integrate to teach the competencies. (Thicker lines represent a stronger connection and dotted lines represent weaker connection)

The Adjunct Publication of the 35th Annual ACM Symposium on User Interface Software and Technology

Figure 1: We present ReflectiveMaker-a toolkit for experts and educators to design refection exer... more Figure 1: We present ReflectiveMaker-a toolkit for experts and educators to design refection exercises for novice learners in makerspaces. Experts and educators can use ReflectiveMaker to design the refection prompts during fabrication activities, sense the user's activities, identify suitable events for prompting refection, record the user's refections, and analyze data on their learning progress.

Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2017.Thesis: S.M... more Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2017.Thesis: S.M., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2017.This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.Cataloged from student-submitted PDF version of thesis.Includes bibliographical references (pages 97-99).The vision of this research is to propose a novel computational framework to study Creative Thinking. If we are to embed machines with creative thinking abilities, then we first need to study the evanescent nature of human creative thinking. Creative thinking is neither entirely random nor strictly logical, making it difficult to t its computation into structured logical models of thinking. Given this conundrum, how can we computationally study the process of thinking creatively? In this research, I first present the current scientific de...

CHI Conference on Human Factors in Computing Systems Extended Abstracts, Apr 27, 2022

The Adjunct Publication of the 35th Annual ACM Symposium on User Interface Software and Technology

Figure 1: My research lies at the intersection of system design, learning sciences, and technolog... more Figure 1: My research lies at the intersection of system design, learning sciences, and technologies that support learning of physical skills. In particular, I have worked on three sets of projects-(1) adaptive learning of motor skills, (2) game-based learning for fabrication skills, and (3) refection-based learning of maker skills.

CHI Conference on Human Factors in Computing Systems

Designing Interactive Systems Conference

Figure 1: (a) Before buying sensors, makers can visualize sensor data from the datasheet to get a... more Figure 1: (a) Before buying sensors, makers can visualize sensor data from the datasheet to get a frst idea of what sensors can sense. (b) Before physically building the prototype, makers can visualize sensor data in AR to see what sensors can sense in the context in which the prototype will be used. (c) After assembling the physical prototype, makers can visualize live data either in the 3D editor or via AR to verify that the sensors work as expected and to make further changes as needed.

The vision of this research is to propose a novel computational framework to study Creative Think... more The vision of this research is to propose a novel computational framework to study Creative Thinking. If we are to embed machines with creative thinking abilities, then we first need to study the evanescent nature of human creative thinking. Creative thinking is neither entirely random nor strictly logical, making it difficult to fit its computation into structured logical models of thinking. Given this conundrum, how can we computationally study the process of thinking creatively? In this research, I first present the current scientific definitions of creative thinking. Through literary survey of cognitive, computational and design thinking frameworks, I identify the missing links between human creativity and AI models of creative thinking. I assert that creative thinking is result of two features of human intelligence, cognitive diversity and social interaction. Cognitive diversity or the ability to parse knowledge in different ways is a crucial aspect of creative thinking. Furthe...

Creativity and Cognition, 2021

The primary objective of the research is to study the non-linear behavior of irregular tensegrity... more The primary objective of the research is to study the non-linear behavior of irregular tensegrity structures and formulate a computational generative, evaluative and algorithmic method to design a structurally dynamic tensegrity system, with inherent potential to adapt to the varying contexts and its respective demands, requirements and spatial needs.

Many motor skills that people learn throughout their lives involve mastering a physical tool, suc... more Many motor skills that people learn throughout their lives involve mastering a physical tool, such as riding a bike, writing with a pen, or playing basketball. To reduce the level of difficulty, learners use physical learning aids, such as training wheels for a bike, that provide physical support. To date, these learning aids only come in predefined levels: For instance, training wheels are either mounted or taken off. This jump from beginner to expert level makes the transition difficult for learners. In this paper, we address this challenge by adapting the physical tool according to the learner’s progress. For instance, while learning to ride a bike, we monitor learners’ balancing skills and as they improve, we gradually lift the training wheels to reduce support and increase the difficulty. Thus, our approach enables a step-by-step transition from beginner to expert level that, similar to existing adaptive learning systems for math and language skills, is personalized for each in...