Chapter 1. Introduction 1
6.2 Fulfillment of objectives
systematically two parameters were identified by Design pedagogues for specifically assessing labelled image-based pattern of creative responses. These features support finding relevance between question and labelled image-based pattern of creative responses and uniqueness of a response.
ix. A computational model was designed and developed to evaluate novelty in labelled image-based pattern of creative responses. This model would support pedagogues to consistently measure novelty in mass examinations.
x. Literature findings suggests seven dimensions of evaluating image-based pattern of creative responses (Berbague et al., 2021; Camburn et al., 2020; Chaudhuri et al., 2020, 2021b; Demirkan & Afacan, 2012; Schumann et al., 1996; Takai et al., 2015), while systematically three parameters were identified by Design pedagogues for specifically assessing annotated image-based pattern of creative responses in mass examination of Design education. These features would support language processing, finding the relevance between question and annotated image-based pattern of creative responses, and uniqueness of a response.
xi. A computational model was designed and developed to evaluate novelty in annotated image-based pattern of creative responses. This model would support pedagogues to consistently measure novelty in mass examinations of Design education.
xii. The performance metric of the proposed models for evaluating descriptive, labelled image-based, and annotated image-based pattern of creative responses were measured.
The MAE of these models were satisfactory as negligible difference was found between the outcome of the models and experts.
xiii. The proposed model comprise multiple self-contained pre-defined models. A comparative study was conducted among the baseline models, and the best-performing model was considered and made part of the proposed model.
Creative question is a significant component in Design entrance examination that triggers creativity in students. There are multiple types of questions and majority of them try to extract learning and knowledge from students. Creative question is an art and science that instigates creative response among students. Literature review and mixed-method research technique was applied to identify creative questions that invokes creative response, which was elaborated in Chapter 1 and 2. Thus, research objective 1 was fulfilled.
Objective 2: To identify variables of questions that has the potential to instigate creative responses among students.
Systematically, twenty-two variables of questions were identified that have the potential to instigate creative response among students. Initially, interview technique was applied to identify the features. Subsequently, their data was transcribed into open codes, clustered, and labelled. Finally, frequency analysis was conducted to identify the repetition of codes to establish their significance. This is described in Chapter 2. Thus, research objective 2 was fulfilled.
Objective 3: To design a digitized system to identify creative questions that has the potential to instigate creative responses among students.
An automated system was designed and developed to identify creative questions that has the potential of capturing creative aptitude. The system is based on the variables identified for creative questions. The system was validated by estimating the inter-rater reliability of the outcome of the model and experts. This study was elaborated in Chapter 2. Thus, research objective 3 was fulfilled.
Objective 4 & 5: To examine the role of novelty in assessment of creative aptitude & to examine types of responses in evaluating novelty in creative aptitude.
Novelty is associated with newness of a response. Understanding novelty and the manual process of evaluating aptitude for choosing students appearing in mass examination of Design entrance tests were elaborated in Chapter 1. This chapter also highlighted the objective and subjective types of questions. Subjective types of questions expect responses based on one’s choice and persuasion. This thesis focussed on subjective questions and assessing their open- ended responses based on certain constraints. Further, it revealed the pattern of creative
responses viz. descriptive, labelled image-based, and annotated image-based pattern of creative responses. Thus, research objective 4 and 5 was fulfilled.
Objective 6: To identify the factors of novelty in creative aptitude evaluation.
Initially, the commonly referred factors of novelty were identified from literature review.
Further, a questionnaire-based survey was conducted to find the subfactors of novelty in creative aptitude evaluation. Five subfactors of novelty in mass examination were identified for descriptive pattern of creative response viz., grammatical mistakes, misspellings, relevance between question and their responses, coherence in responses, and relative uniqueness of a response. Two subfactors of novelty in mass examination were identified for labelled image- based pattern of creative responses viz., relevance between question and a response, and relative uniqueness of a response. Three subfactors of novelty in mass examination were identified for annotated image-based pattern of creative responses viz., language processing, relevance between question and their responses, and relative uniqueness of a response. The systematic identification of the factors of evaluating novelty associated with various pattern of creative responses has been reported in Chapter 3, 4, and 5. Thus, research objective 6 was fulfilled.
Objective 7: To design a digitized system for novelty assessment in creative aptitude.
An automated system was designed and developed to evaluate creative aptitude based on the factors of novelty. A system is designed for evaluating multiple pattern of creative responses viz., descriptive pattern of creative response, labelled image-based pattern of creative response, and annotated image-based pattern of creative response. The models are validated by comparing their outcomes with human experts, which exhibited negligible differences. The computational models for various creative responses have been briefly described in Chapter 3, 4, and 5. Thus, research objective 7 was fulfilled.