scholarly journals Semantic Measures for Enhancing Creativity in Design Education

2019 ◽  
Vol 1 (1) ◽  
pp. 369-378
Author(s):  
Georgi V. Georgiev ◽  
Hernan Casakin
Keyword(s):  
Information Content ◽  
Semantic Similarity ◽  
Significant Relationship ◽  
Design Education ◽  
Semantic Analysis ◽  
Semantic Content ◽  
Design Studio ◽  
Design Activity ◽  
Design Creativity ◽  
Verbal Data

AbstractAnalysing verbal data produced during the design activity is helpful to gain a better understanding of design creativity. To understand exchange of information in terms of creative outcomes, a semantic analysis approach was used to measure the semantic content of communications between students and teachers. The goal was to use this tool to analyse design conversations, and to investigate their relation to design creativity, assessed in terms of originality, usability, feasibility, aesthetics, elaboration, overall value and overall creativity. Abstraction, Polysemy, Information Content and Semantic Similarity were employed to explore 35 design conversations from the DTRS10 dataset. Main findings suggest that a significant relationship exists between Information Content and Originality, and between Information Content and Overall creativity of the produced design outcomes. Significant relations were also found between Abstraction, Polysemy, Information Content, and Feasibility, as well as between Semantic Similarity and Overall Value of the outcomes. Implications for the use of semantic measures for encouraging creativity in the design studio are discussed.

scholarly journals Formal Learning Sequences and Progression in the Studio: A Framework for Digital Design Education

10.28945/3406 ◽  
2016 ◽  
Vol 15 ◽  
pp. 035-052
Author(s):  
Pontus Wärnestål
Keyword(s):  
Design Education ◽  
Digital Design ◽  
Design Studio ◽  
Formal Learning ◽  
User Centered Design ◽  
Learning Sequence ◽  
Sustainable Solutions ◽  
Design Creativity ◽  
Wide Range ◽  
Learning Sequences

This paper examines how to leverage the design studio learning environment throughout long-term Digital Design education in order to support students to progress from tactical, well-defined, device-centric routine design, to confidently design sustainable solutions for strategic, complex, problems for a wide range of devices and platforms in the digital space. We present a framework derived from literature on design, creativity, and theories on learning that: (a) implements a theory of formal learning sequences as a user-centered design process in the studio; and (b) describes design challenge progressions in the design studio environment modeled in seven dimensions. The framework can be used as a tool for designing, evaluating, and communicating course progressions within – and between series of – design studio courses. This approach is evaluated by implementing a formal learning sequence framework in a series of design studio courses that progress in an undergraduate design-oriented Informatics program. Reflections from students, teachers, and external clients indicate high student motivation and learning goal achievement, high teacher satisfaction and skill development, and high satisfaction among external clients.

An Efficient Approach for Ranking of Semantic Web Documents by Computing Semantic Similarity and Using HCS Clustering

2021 ◽  
Vol 5 (1) ◽  
pp. 45-56
Author(s):  
Poonam Chahal ◽  
Manjeet Singh
Keyword(s):  
Semantic Web ◽  
Semantic Similarity ◽  
Semantic Analysis ◽  
Semantic Content ◽  
Graph Representation ◽  
Graphical Form ◽  
Theoretic Approach ◽  
Connected Subgraph ◽  
Web Documents ◽  
The Web

In today's era, with the availability of a huge amount of dynamic information available in world wide web (WWW), it is complex for the user to retrieve or search the relevant information. One of the techniques used in information retrieval is clustering, and then the ranking of the web documents is done to provide user the information as per their query. In this paper, semantic similarity score of Semantic Web documents is computed by using the semantic-based similarity feature combining the latent semantic analysis (LSA) and latent relational analysis (LRA). The LSA and LRA help to determine the relevant concepts and relationships between the concepts which further correspond to the words and relationships between these words. The extracted interrelated concepts are represented by the graph further representing the semantic content of the web document. From this graph representation for each document, the HCS algorithm of clustering is used to extract the most connected subgraph for constructing the different number of clusters which is according to the information-theoretic approach. The web documents present in clusters in graphical form are ranked by using the text-rank method in combination with the proposed method. The experimental analysis is done by using the benchmark datasets OpinRank. The performance of the approach on ranking of web documents using semantic-based clustering has shown promising results.

Computationally Derived Adaptive Inspirational Stimuli for Real-Time Design Support During Concept Generation

2019 ◽  
Author(s):  
Kosa Goucher-Lambert ◽  
Joshua T. Gyory ◽  
Kenneth Kotovsky ◽  
Jonathan Cagan
Keyword(s):  
Real Time ◽  
Semantic Similarity ◽  
Semantic Analysis ◽  
A Priori ◽  
Similarity Measures ◽  
Design Activity ◽  
Concept Generation ◽  
Experimental Conditions ◽  
Final Design ◽  
The Impact

Abstract Design activity can be supported using inspirational stimuli (e.g., analogies, patents, etc.), by helping designers overcome impasses or in generating solutions with more positive characteristics during ideation. Design researchers typically generate inspirational stimuli a priori in order to investigate their impact. However, for a chosen stimulus to possess maximal utility, it should automatically reflect the current and ongoing progress of the designer. In this work, designers receive computationally selected inspirational stimuli midway through an ideation session in response to the state of their current solution. Sourced from a broad database of related example solutions, the semantic similarity between the content of the current design and concepts within the database determine which potential stimulus is received. Designers receive a particular stimulus based on three experimental conditions: a semantically near stimulus, a semantically far stimulus, or no stimulus (control). Results indicate that adaptive inspirational stimuli can be determined using Latent Semantic Analysis (LSA) and that semantic similarity measures are a promising approach for real-time monitoring of the design process. The ability to achieve differentiable near vs. far stimuli was validated using both semantic cosine similarity values and participant self-response ratings. As a further contribution, this work also explores the impact of different types of adaptive inspirational stimuli on design outcomes. Here, near inspirational stimuli increase the feasibility of design solutions. Results also demonstrate the significant impact of the overall inspirational stimulus innovativeness on final design outcomes, which may be greater than differences across individual sub-dimensions.

scholarly journals Adaptive Inspirational Design Stimuli: Using Design Output to Computationally Search for Stimuli That Impact Concept Generation

2020 ◽  
Vol 142 (9) ◽  
Author(s):  
Kosa Goucher-Lambert ◽  
Joshua T. Gyory ◽  
Kenneth Kotovsky ◽  
Jonathan Cagan
Keyword(s):  
Semantic Similarity ◽  
Semantic Analysis ◽  
Similarity Measures ◽  
Design Activity ◽  
Concept Generation ◽  
Experimental Conditions ◽  
Final Design ◽  
Design Solutions ◽  
Design Innovation ◽  
The Impact

Abstract Design activity can be supported using inspirational stimuli (e.g., analogies, patents) by helping designers overcome impasses or in generating solutions with more positive characteristics during ideation. Design researchers typically generate inspirational stimuli a priori in order to investigate their impact. However, for a chosen stimulus to possess maximal utility, it should automatically reflect the current and ongoing progress of the designer. In this work, designers receive computationally selected inspirational stimuli midway through an ideation session in response to the contents of their current solution. Sourced from a broad database of related example solutions, the semantic similarity between the content of the current design and concepts within the database determines which potential stimulus is received. Designers receive a particular stimulus based on three experimental conditions: a semantically near stimulus, a semantically far stimulus, or no stimulus (control). Results indicate that adaptive inspirational stimuli can be determined using latent semantic analysis (LSA) and that semantic similarity measures are a promising approach for real-time monitoring of the design process. The ability to achieve differentiable near versus far stimuli was validated using both semantic cosine similarity values and participant self-response ratings. As a further contribution, this work also explores the impact of different types of adaptive inspirational stimuli on design outcomes using a newly introduced “design innovation” measure. The design innovation measure mathematically captures the overall goodness of a design concept by uniquely combining expert ratings across easier to evaluate subdimensions of feasibility, usefulness, and novelty. While results demonstrate that near inspirational stimuli increase the feasibility of design solutions, they also show the significant impact of the overall inspirational stimulus innovativeness on final design outcomes. In fact, participants are more likely to generate innovative final design solutions when given innovative inspirational stimuli, regardless of their experimental condition.

scholarly journals APPROACHES IN DESIGN EDUCATION: THE ROLE OF PATTERNS AND SCENARIOS IN THE DESIGN STUDIO

2016 ◽  
Vol 69 (1) ◽  
pp. 6-21
Author(s):  
Hernan Casakin ◽  
Arjan van Timmeren ◽  
Petra Badke-Schaub
Keyword(s):  
Problem Solving ◽  
Design Patterns ◽  
Design Education ◽  
Design Thinking ◽  
Design Studio ◽  
Design Activity ◽  
Educational Setting ◽  
Educational Approach ◽  
Design Problems ◽  
Functional Perspective

The studio is the educational setting where architectural students dedicate a large part of their study career working individually and in groups. Supporting students with adequate methods to deal with ill-defined problems in the design studio is a major challenge for design education. Whereas different approaches such as using design patterns and developing scenarios are reported to improve the design activity, they were never investigated in the design studio. An empirical investigation was conducted in order to explore whether and how scenarios and patterns can help students in developing a useful knowledge base and enhance their abilities to solve design problems in the design studio. Students were requested to solve a series of design problems using these educational methods, while working individually and as a team. They were asked to produce as many design ideas as possible, while in the team setting were instructed to think aloud. The data assessed is gathered from surveys, problem solving sessions, and interviews. Thus, qualitative and quantitative analyses had to be done to find out about the different impact of the two methods in design. The results showed that as an educational approach, patterns aided in defining problems and analyzing idea solutions, mainly from a technical and functional perspective. Scenarios, on the other hand, were helpful to generate new ideas, and to enhance design creativity. Independently of the pedagogical method used in the design studio, working in teams showed to be central to enrich and enhance many aspects of the design activity. The findings have important implications for intervention programs in the design studio. Key words: design thinking, design studio, design education, educational setting, problem solving session, students teamwork.

scholarly journals THE INFLUENCE OF DESIGN BRIEF INFORMATION ON CREATIVE OUTCOMES BY NOVICE AND ADVANCED STUDENTS

2021 ◽  
Vol 1 ◽  
pp. 3041-3050
Author(s):  
Georgios Koronis ◽  
Hernan Casakin ◽  
Arlindo Silva ◽  
Jacob Kai Siang Kang
Keyword(s):  
Design Education ◽  
Design Problems ◽  
Frame Design ◽  
Design Creativity ◽  
Abstract Representations ◽  
Advanced Students ◽  
Different Types ◽  
Fishbone Diagram ◽  
Design Expertise ◽  
Novel Design

AbstractThis study centers on using different types of brief information to support creative outcomes in architectural and engineering design and its relation to design expertise. We explore the influence of design briefs characterized by abstract representations and/or instructions to frame design problems on the creativity of concept sketches produced by novice and advanced students. Abstract representations of problem requirements served as stimuli to encourage associative thinking and knowledge transfer. The Ishikawa/Fishbone Diagram was used to foster design restructuring and to modify viewpoints about the main design drives and goals. The design outcomes generated by novice and advanced engineering/architecture students were assessed for their creativity using a pairwise experimental design. Results indicated that advanced students generated more novel design solutions while also contributing the most useful solutions overall. Implications for creativity in design education and professional practice are presented. Educational programs aimed at promoting creativity in the design studio may find it helpful to consider that the way design briefs are constructed can either promote or inhibit different aspects of design creativity.

scholarly journals A System to Assess the Semantic Content of Student Essays

2001 ◽  
Vol 24 (3) ◽  
pp. 305-320 ◽  
Author(s):  
Benoit Lemaire ◽  
Philippe Dessus
Keyword(s):  
Latent Semantic Analysis ◽  
Semantic Analysis ◽  
Dimensional Space ◽  
Semantic Content ◽  
High Dimensional ◽  
High Dimensional Space

This paper presents Apex, a system that can automatically assess a student essay based on its content. It relies on Latent Semantic Analysis, a tool which is used to represent the meaning of words as vectors in a high-dimensional space. By comparing an essay and the text of a given course on a semantic basis, our system can measure how well the essay matches the text. Various assessments are presented to the student regarding the topic, the outline and the coherence of the essay. Our experiments yield promising results.

DISTANCE-WISE PATHWAY DISCOVERY FROM PROTEIN–PROTEIN INTERACTION NETWORKS WEIGHTED BY SEMANTIC SIMILARITY

2014 ◽  
Vol 12 (01) ◽  
pp. 1450004 ◽  
Author(s):  
SLAVKA JAROMERSKA ◽  
PETR PRAUS ◽  
YOUNG-RAE CHO
Keyword(s):  
Signaling Pathways ◽  
Semantic Similarity ◽  
Protein Interaction ◽  
Protein Pair ◽  
Semantic Analysis ◽  
Topological Analysis ◽  
Cellular Mechanisms ◽  
Semantic Similarity Measure ◽  
Protein Protein Interaction ◽  
Ppi Networks

Reconstruction of signaling pathways is crucial for understanding cellular mechanisms. A pathway is represented as a path of a signaling cascade involving a series of proteins to perform a particular function. Since a protein pair involved in signaling and response have a strong interaction, putative pathways can be detected from protein–protein interaction (PPI) networks. However, predicting directed pathways from the undirected genome-wide PPI networks has been challenging. We present a novel computational algorithm to efficiently predict signaling pathways from PPI networks given a starting protein and an ending protein. Our approach integrates topological analysis of PPI networks and semantic analysis of PPIs using Gene Ontology data. An advanced semantic similarity measure is used for weighting each interacting protein pair. Our distance-wise algorithm iteratively selects an adjacent protein from a PPI network to build a pathway based on a distance condition. On each iteration, the strength of a hypothetical path passing through a candidate edge is estimated by a local heuristic. We evaluate the performance by comparing the resultant paths to known signaling pathways on yeast. The results show that our approach has higher accuracy and efficiency than previous methods.

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