Subject Matter Specialists Research Articles

A Comic-Based Learning Approach Grounded in Islamic Constructivism: Utilizing Canva to Explore Solar System Concepts

The purpose of this research endeavor is to evaluate the feasibility of comic-based educational media grounded in an Islamic nuanced constructivist framework, employing Canva applications for the instruction of solar system content. The study was carried out in accordance with Thiagarajan's 4D model, engaging seventh-grade students from SMP/MTs. Data were gathered from the feedback of both students and educators, in conjunction with validation from subject matter specialists, media professionals, and religious authorities. The outcomes of the investigation reveal that the material validation from experts achieved a score of 91%, media experts assigned a score of 86%, while religious authorities contributed a score of 82%. These findings signify a commendable degree of validation. In summary, drawing upon the assessments from experts and the affirmative feedback from educators and students, it can be inferred that the comic-based learning media, rooted in an Islamic constructivist paradigm utilizing Canva applications, serves as an efficacious and stimulating educational instrument for imparting knowledge regarding solar system concepts.

Feasibility of a problem-based social constructivism learning model to improve higher-order thinking skills among primary school students

This research aims to demonstrate the results of an experiment on how the Problem-Based Social Constructivism Learning Model (PBSCL) can be developed to effectively promote Higher-Order Thinking Skills (HOTS) among primary school children. The methodology employed in this study was developmental research which involved thorough preliminary studies, meticulous product development and comprehensive product testing stages. Respondents for this study included model experts, language experts, content specialists and practitioners. Data collection instruments used were detailed questionnaires served during the feasibility test. In addition, product testing involved rigorously confirming the findings of product development through extensive expert validation, including learning model expert validation, content or material expert validation, language expert validation and practitioner validation. The results of the assessment on learning design expert validators for the PBSCL learning model indicated that they had high qualifications with the average score being 3.29. Consequently, learning design experts ensured that the criteria were meticulously met by the PBSCL learning model for HOTS improvement. Additionally, subject matter specialists confirmed the appropriateness and effectiveness of using the PBSCL learning model for HOTS improvement. The findings suggest that the PBSCL learning model has significant potential to substantially enhance HOTS among primary school students. However, further investigation is needed to fully validate its effectiveness and practical application in diverse educational settings.

Participatory Assessment of Agriculture Land and Vegetation Associated Issues and Possible Interventions in Gurage Zone, Ethiopia

Land degradation and depletion of natural forests made agriculture unsustainable and threaten communities and ecosystems as a whole. The objective of this participatory assessment was to identify researchable issues related to agricultural land and vegetation cover in Gurage zone. Accordingly, seven representative districts were selected and from each district two representative kebeles were purposively selected. Focus Group Discussion with farmers, development agents and subject matter specialists and direct observation were important primary sources of information. The survey result depicts in the Gurage zone land degradation, undulating steep slope topography, small and overwhelmed land tenure, inappropriate land use system, cultural landscape mismanagement, deforestation of indigenous trees and expansion of eucalyptus tree, and decreasing enset production are the major identified problems associated with land use and vegetation cover of the study area. In the mixed farming system, enset is produced as a homestead farm and its coverage is decreasing due to disease, lack of processing machines, and shortage of organic matter. Due to the expansion of eucalyptus and land use change, the majority of native trees are disappearing or decreasing in area coverage. Therefore, enset and eucalyptus require suitable policy attention. In the mountainous areas of Gurage; limited land availability, soil degradation, shortage of appropriate farm technologies, water scarcity, lack of knowledge for alpine agriculture and inconvenient topography for mechanized farming machines issues threaten agriculture of area. Despite the fact that there are few attempts to control land degradation; the issue still needs much attention. Appropriate agricultural technologies and knowledge suited for mountain agriculture, dense populations, enset-based farming systems, and small land tenure are important priority research focus areas for future research.

Construction and Standardization of Knowledge Test to Measure the Knowledge Level of Farmers on Rice Crop Cultivation

A study was designed to develop a standardized test to measure the knowledge of rice farmers. Pertinent items covering every aspect of rice cultivation were collected with the help of subject matter specialists, progressive farmers, and scientists along with related literature. After getting experts opinion, items were subjected to difficulty index, discrimination index, correlation, reliability and validity. Items with 20-80 of difficulty level, items with 0.20-0.80 discrimination index and significant either at 1 percent or 5 percent level point in biserial correlation were selected and admitted to rice to measure knowledge level on rice cultivation. A total of 47 items were included in the final knowledge test to measure the knowledge level of farmers in rice cultivation.

FEASIBILITY OF THE FUNGI MATERIAL TEACHING MODULE AS A LEARNING RESOURCE FOR HIGH SCHOOL STUDENTS

This study investigates the utilization of Teaching Modules as a pedagogical tool in biology education, with a specific focus on the subject of Fungi. Recognized for their practicality and portability, Teaching Modules are deemed as efficacious educational aids to facilitate learning endeavors, both within classroom settings and in practical field applications. The research centers on the development and validation of Teaching Modules tailored for the Fungi curriculum, targeting students in the tenth grade of high school. Employing the Research and Development (R&D) methodology, this inquiry rigorously evaluates Teaching Modules across content, language, and presentation dimensions. Expert evaluations, featuring input from subject matter specialists and media professionals, underscore the Teaching Modules' commendable quality, achieving a validation score of 90%. Conclusively, this investigation affirms the Teaching Modules' substantive merit and validity as educational media, particularly in assisting students in discerning diverse forms of Basidiomycota Fungi.

Development and Validation of Hospital Mental Health Screen to Detect Psychiatric Morbidity in Medically Ill Patients in India

Background: Psychiatric morbidities often go unnoticed in medically ill patients. It is essential to screen patients with medical morbidity so that they can be referred to psychiatrists for early interventions in general hospitals in India. There is a potential lacuna in terms of the availability of a scale that can aptly identify psychiatric symptoms in medically ill patients beyond depression or anxiety, especially in low-resource settings like India. Aim: The aim was to detect psychiatric morbidity in medically ill patients in India. Methodology: Items were generated using deductive and inductive approaches. Item-Content Validity Index (I-CVI) and Scale-Content Validity Index/Universal Agreement (S-CVI/UA) were computed by involving eight subject matter specialists. The tool was circulated to 397 medically ill patients for computing The exploratory factor analysis (EFA). Domain-wise reliability using Cronbach’s alpha was calculated for six factors. The concurrent criterion validity of the Hospital Mental Health Screen (HMHS) tool was calculated by the receiver operating curve (ROC) against the gold standard of any psychiatric morbidity diagnosed by two psychiatrists in 397 medically ill patients. We used IBM SPSS version 23. Results: Initially, 34 items were generated. At the I-CVI threshold of 79%, seven items were discarded. The S-CVI/UA of the scale was 85.1%. The Kaiser–Meier–Olkin Measure of Sampling Adequacy (KMO MSA) was found to be 0.916. At a factor loading threshold of 0.4 and an eigenvalue above 1, a six-factor structure was extracted using principal component analysis and varimax rotation. Domain-wise reliability was computed, which was between 0.657 and 0.840. The final tool consisted of 27 Likert items (0 = never to 4 = always). Using the ROC curve at the 19.5 threshold, 91.4% of the positive outcomes were correctly classified and 9.5% of the adverse outcomes were expected to be incorrectly identified by the HMHS screening tool. Conclusion: HMHS is a valid and reliable tool with good screening properties, designed especially for the Indian setting. This scale can assist in identifying psychiatric morbidity in medically ill patients in low-resource settings. There is further scope for performing confirmatory factor analysis (CFA) to reinforce the factor structure of HMHS.

Depression among Women during Menopause and Its Effect

Major depressive disorder (MDD) is a serious medical condition that affects how people feel, how they think and how they behave. In developed countries, menopause usually begins between the ages 40 and 58. The average age in the United States is 52 years. For some women, menopause (perimenopause), or the "change of life", is a rollercoaster of physical and emotional highs and lows. The so-called "change of life" is accompanied by a variety of symptoms, such as hot flashes and insomnia, mood swings and depression. When women experience sudden hormonal changes, such as menopausal changes, puberty and postpartum changes, and even changes in their monthly cycles, they are at an increased risk for developing depression. In fact, women are three times more likely to develop depression than men. The main focus of this study was on “depression among women during menopause and its effect”. The study included women aged 45-55 years. For the study, a sample of sixty women from Madakasira village in the Sathya Sai district comprised the sample. Under the direction of subject matter specialists, the researcher created a questionnaire, which was pre-tested on a different sample before being given to the real sample. According to the study, women experienced anxiety and despair throughout menopause.

Deep learning technique for plant disease detection

A nation's economy is primarily reliant on agricultural growth. However, several plant diseases seriously impair crop growth, both in terms of quantity and quality. Due to a lack of subject matter specialists and low contrast data, accurate diagnosis of many diseases by hand is highly difficult and time-consuming. The farm management system is therefore looking for a method for automatically detecting early illnesses. To overcome these challenges and correctly classify the different diseases, an efficient and small deep learning-based framework (E-GreenNet) is proposed. A MobileNetV3Small model is used as the foundation of our end-to-end architecture to produce finely tuned, discriminative, and noticeable features. Furthermore, the new plant composite (PC), plantvillage (PV), and data repository of leaf images (DRLI) datasets are used to independently train our proposed model, and test samples are used to evaluate its actual performance. The suggested model achieved accuracy rates of 1.00 percent, 0.96 percent, and 0.99 percent on the given datasets after a rigorous experimental study. Additionally, a comparative investigation of our proposed technique against the state-of-the-art (SOTA) reveals extremely high discriminative scores.

Deep learning technique for plant disease detection

A nation's economy is primarily reliant on agricultural growth. However, several plant diseases seriously impair crop growth, both in terms of quantity and quality. Due to a lack of subject matter specialists and low contrast data, accurate diagnosis of many diseases by hand is highly difficult and time-consuming. The farm management system is therefore looking for a method for automatically detecting early illnesses. To overcome these challenges and correctly classify the different diseases, an efficient and small deep learning-based framework (E-GreenNet) is proposed. A MobileNetV3Small model is used as the foundation of our end-to-end architecture to produce finely tuned, discriminative, and noticeable features. Furthermore, the new plant composite (PC), plantvillage (PV), and data repository of leaf images (DRLI) datasets are used to independently train our proposed model, and test samples are used to evaluate its actual performance. The suggested model achieved accuracy rates of 1.00 percent, 0.96 percent, and 0.99 percent on the given datasets after a rigorous experimental study. Additionally, a comparative investigation of our proposed technique against the state-of-the-art (SOTA) reveals extremely high discriminative scores.

Integrated Pest Management Technology in Cotton in Parbhani District of Maharashtra State: An Economic Analysis

The present investigation pertinent to this study was conducted in Manwat and Parbhani tahasil of Parbhani district. For the present study 70 cotton growers who follows IPM technology were selected in consultation with KVK subject matter specialists, Officials of State Agriculture department and Extension Agronomists. Further the sample of 70 farmers were divided into three categories viz., Low adopters, medium adopters, high adopters, based on their levels of adoption. To assess extent of adoption of various IPM technology of cotton the concept of TAI was used According to the study, only 17.14 per cent respondents were high level of IPM technology adopters, 14.28 per cent have adopted IPM at low level while highest i.e. 68.57 per cent farmers had adopted IPM technology at medium level.

Development of Mobile App as an Educational Tool for Understanding Nanomedicine

Nanomedicine, an emerging field at the intersection of nanotechnology and medicine, holds great promise for revolutionizing healthcare by enabling targeted diagnostics and treatments at the molecular level. However, due to its complex nature, understanding nanomedicine concepts and applications can be challenging for healthcare professionals, researchers, and the general public. To bridge this knowledge gap and promote awareness, a mobile application was developed to enhance the understanding of nanomedicine, and named it "MyNanoRia". The MyNanoRia was developed by initially designing suitable content, compiling information and creating the apps using Unity platform, specifically for the Android operating system. The MyNanoRia provides users with readily available knowledge about nanomedicine's concepts, methods, and applications as an interactive educational tool. Specific facets of nanotechnology, nanomedicine, nanomaterials, and cancer are covered in this app. MyNanoRia also includes definitions for particular keywords. This app's creation required consulting and validation by subject-matter specialists, such as chemists, biologists, and medical scientists. The development of MyNanoRia is challenging since nanotechnology is a multidiscipline topic that indeed emphasizes scientific understanding, but the intended users are those who know little to nothing about it. Creating the MyNanoRia app for understanding nanomedicine seeks to close the knowledge and awareness gap between science and the general public, enabling researchers, healthcare professionals, and the general public to fully value nanotechnology's potential in healthcare.

A Historical-critical Study of the First Latin Translation of the Holy Quran

The Benedictine abbot Peter the Venerable started an effort to study the Holy Quran in the years 1141 and 1142 when he was staying at the Abbey of Cluny. Robert of Ketton was one of the groups he assembled to translate the Islamic scripture. The goal of this campaign was to introduce Islam, which by that time had become a significant political force, to Western Christians. The ultimate objective was to aid missionaries who were trying to convert the people in areas that Christians had recaptured. Based on predetermined goals and duties, the translation was pursued. This essay seeks to shed light on the details of this translation, one of the first in Europe, which was done by individuals with little to no knowledge of Islam, misinterpreting the identities and attitudes of its adherents and acting on false ideological assumptions in order to further their own and their sponsors’ goals. A descriptive critical review is used in this work to illuminate the historical background that contributes to the understanding of the underlying problem. We take into account several viewpoints, most notably James Kritzeck’s, whose critiques aid in clarifying the translation process, and strive to reach a fair conclusion regarding it. Analyzing the translation alone, from a linguistic and cultural perspective, is another important consideration. By providing a critical-historical analysis of the setting, this initiative hopes to make translators and other interested parties aware of the project’s limitations. We defer verification and responses to subject-matter specialists since understanding the goals of this complex endeavor takes specialized knowledge, sufficient time, and consistent effort.

Developing STEM-Based PowToon Animation Videos to Enhance Critical Thinking Skills in Elementary School Students

This article examines the utilization of the PowToon animated film, integrated with the STEM (Science, Technology, Engineering, and Mathematics) approach, in enhancing the critical thinking skills of primary school students. Employing the ADDIE model methodology, this research involved 20 students as its subjects. Data collection techniques included observation, questionnaires, and evaluation of critical thinking skills. During the analysis phase, expert validation served as the foundational consideration, and the results of the students' critical thinking skills test were subsequently analyzed comparatively. The findings revealed that the PowToon animation with the STEM approach received positive feedback from experts, with scores of 92.50% from subject matter specialists, 89.50% from media experts, and 91.00% from linguistic authorities. When the topics of temperature and heat were presented through this animation, a significant improvement in the students' critical thinking abilities was observed. In conclusion, the STEM-based PowToon animation demonstrates its potential as an innovative and effective educational tool.

Examining the Professional Excellence Programme: Inducting University Teachers into the Higher Education System in South Africa

The obligation to increase the standard of instruction and learning falls on academic developers. A crucial part of academic staff development at institutions of higher learning is the induction of academics who are primarily subject matter specialists without the pedagogical abilities to teach effectively in the higher education environment. This qualitative essay investigated how the Professional Excellence Programme (PEP) might be utilised as an induction Short Learning Programme (SLP) for new academics. After finishing the brief SLP, the inductees were given a questionnaire to evaluate the modules (Teaching and Learning, Curriculum Development, and Assessment in Higher Education) and qualitative data was gathered. The study was framed by Wegner’s social learning theory. The research showed that the PEP programme can be an efficient programme to develop academics into university teachers. Since the SLP was accepted by all participants in the study, the study recommended that the Directorate of Teaching and Learning should develop the PEP programme into a credit-bearing postgraduate diploma in higher education at NQF Level 8, which is equivalent to an honours degree. Keywords: Professional excellence, Induction, University teacher, Transformative pedagogy, Academic developer

RiPa-Net: Recognition of Rice Paddy Diseases with Duo-Layers of CNNs Fostered by Feature Transformation and Selection.

Rice paddy diseases significantly reduce the quantity and quality of crops, so it is essential to recognize them quickly and accurately for prevention and control. Deep learning (DL)-based computer-assisted expert systems are encouraging approaches to solving this issue and dealing with the dearth of subject-matter specialists in this area. Nonetheless, a major generalization obstacle is posed by the existence of small discrepancies between various classes of paddy diseases. Numerous studies have used features taken from a single deep layer of an individual complex DL construction with many deep layers and parameters. All of them have relied on spatial knowledge only to learn their recognition models trained with a large number of features. This study suggests a pipeline called "RiPa-Net" based on three lightweight CNNs that can identify and categorize nine paddy diseases as well as healthy paddy. The suggested pipeline gathers features from two different layers of each of the CNNs. Moreover, the suggested method additionally applies the dual-tree complex wavelet transform (DTCWT) to the deep features of the first layer to obtain spectral-temporal information. Additionally, it incorporates the deep features of the first layer of the three CNNs using principal component analysis (PCA) and discrete cosine transform (DCT) transformation methods, which reduce the dimension of the first layer features. The second layer's spatial deep features are then combined with these fused time-frequency deep features. After that, a feature selection process is introduced to reduce the size of the feature vector and choose only those features that have a significant impact on the recognition process, thereby further reducing recognition complexity. According to the results, combining deep features from two layers of different lightweight CNNs can improve recognition accuracy. Performance also improves as a result of the acquired spatial-spectral-temporal information used to learn models. Using 300 features, the cubic support vector machine (SVM) achieves an outstanding accuracy of 97.5%. The competitive ability of the suggested pipeline is confirmed by a comparison of the experimental results with findings from previously conducted research on the recognition of paddy diseases.

Constraints Faced by the Groundnut Growers in Adoption of Cluster Frontline Demonstration of Villupuram District

India is one of the largest producers of oilseeds in the world and occupies an important position in the Indian agricultural economy. The productivity of groundnut farming is currently declining due to pest and disease attacks, use of old and traditional low-yielding varieties. To tackle the issues demonstrations on cluster mode are essential. Cluster Frontline Demonstration (CFLD) is conducted by Subject Matter Specialists (SMSs) and scientists in a systemic manner on selected farmers field to spread the new variety and groundnut production technologies. The ICAR- KVK, Tindivanam had organized CFLDs on groundnut crop in two villages viz., Nolambur and Kilmavilangai. Therefore, the study aimed to know the profile characteristics of CFLD beneficiary farmers and to encounter the major constraints faced by groundnut growers. To get an adequate sample size, 60 CFLD beneficiaries were selected randomly for the present study. The data were collected by using a pre-tested interview schedule. Garrett’s ranking technique and percentage analysis were used to analyze the data for meaning interpretation. The majority of beneficiaries belonged to middle age category (61.66%), majority of male beneficiaries (80.00%), educated upto middle school (40.00%), land holdings of 1 to 2 ha (68.33%) as small land, 20- 30 years of farming experience in oilseeds (80.00%), participated in one training (66.67%), medium level of extension agency contact (66.67%) and mass media exposure (56.67%), 55 per cent of farmers were adopted new practices after the successful adoption of other members. The major constraints include poor labour availability, poor transport facilities, lack of proper marketing channels and lack of technical knowledge. Hence, CFLD showed that medium to high level profile characteristics and improved adoption of new technologies.

Об одном из аспектов подготовки профильных специалистов в современных лингвистических вузах

The article identifies the factors that determine the need to expand the scope of linguistic and intercultural competencies of subject-matter specialists — translators or interpreters and teachers of foreign languages trained in linguistic universities, towards multilingualism and multiculturalism. The relevance of addressing this topic is due to professional activities of the named subject-matter specialists in the conditions of polyglossia, which is characteristic both for educational and scientific environment of recent decades, and for the sphere of international and interstate relations. Author names the main circumstances associated with the organization of teaching foreign languages in modern universities. These circumstances, from her point of view, hinder implementation of shift towards multilingualism and multiculturalism in training the above named specialists. The solution of the outlined problem, according to the author, is primarily associated with governmental regulation in this area, as well as taking into account international experience in studying foreign languages and applying best methods for teaching them in conditions of university polyglossia.

An Expert-Opinion-Based Evaluation Framework for Sustainable Technology-Enhanced Learning Using Z-Numbers and Fuzzy Logarithm Methodology of Additive Weights

As technology continues to shape the landscape of education, the need for effective evaluation frameworks for sustainable technology-enhanced learning (TEL) becomes increasingly vital. This study presents an expert-opinion-based evaluation framework, utilizing Z-numbers and the fuzzy logarithm methodology of additive weights (LMAW), to assess the sustainability of TEL approaches. This framework focuses on four main criteria: cloud services compliance, cloud M-Learning essentials, system and technological advancement, and organizations management readiness. Additionally, it incorporates 17 sub-criteria to provide a comprehensive evaluation of the system. Drawing on the expertise of subject matter specialists, the evaluation framework utilizes Z-numbers to account for the inherent uncertainty and imprecision in expert judgments. The fuzzy LMAW is applied to calculate the overall scores for each criterion and sub-criterion, enabling a quantitative measure of their importance in the evaluation process. The findings of this study will contribute to the development of a robust and scientifically rigorous evaluation framework for sustainable TEL. By incorporating expert opinions and employing Z-LMAW, decision-makers and stakeholders can objectively assess the sustainability of TEL systems. This framework holds promise for informing the design and implementation of strategies to enhance the quality, compliance, and technological advancements in TEL environments.

Effect of Teachers’ Work-Life Balance on Performance of Secondary School Students in Kwale County, Kenya

The study examined the impact of teacher’s work-life balance and effective time management on students' academic performance in public secondary schools in Kwale county, Kenya. In the five years prior to the study, the county had a low mean score of a dismal 7% in 2016 which experienced a modest increase to only 10.5% in 2020. Teachers’ contribution in guiding students to good performance is not debatable and is well acknowledged the world over. The role of a teacher as a mentor, a guide, a role model, a parent, a vision carrier and all the good deeds attributable to a good teacher are what translates to a successful student. All people who have gone through school education attest to the fact that were it not for their teachers, they would not have made it to where they reached. However, when issues in life affect a teacher’s attention to their work, it inadvertently affects their efficiency in service delivery and consequently, their students’ performance. The purpose of this study was to establish the effect of teachers' work-life balance and time management in enhancing students' academic performance in secondary schools in Kwale County, Kenya. Further, the study sought to establish students’ perception of their teachers planning and execution of teaching and identify any challenges facing teachers that would impact on poor performance of the students. The target population was 7,598 respondents comprising of 98 principals, 960 teachers and 6,540 form four students from public secondary schools in Kwale County. The sample size was determined using Krejcie and Morgan (1970) table where a sample of 274 teachers, 364 form four students and 29 principals was established. Data was collected using a structured questionnaire. Validity of the research instrument was established after being examined for logical content by university subject matter specialists. Internal reliability was estimated through Cronbach’s alpha coefficient of reliability at α= .83 while external reliability was estimated by using Pearsons’s correlation coefficient in which a coefficient of r = .81 was realized. Regression analysis was carried out on quantitative data and descriptive statistics used to establish relationships between the dependent and the independent variables. The findings were presented as proportions in tables and discussed. The study established a statistically significance relationship of effects of teachers’ work life balance on students’ performance (R 2 =-0.172, F=50.773, p=0.000) as well as students’ perceptions of the teachers work planning on their performance at (R 2 =0.119, F=317.541, P=0.000). This meant that about 17.2 percent of students performance could be attributed to teacher’s work-life balancing and 11.9% would be attributed to teachers’ ability to plan and manage their work according to their students, respectively, other factors constant. On the challenges affecting the teacher that would impact on a students’ academic performance, the study further found a statistically significant relationship (R 2 =0.238, F=53.305, P=0.000). This means that about 23.8 percent of students performance was impacted positively or negatively by challenges facing their teachers. The study concluded that teachers must balance the personal and work life well and manage their time if students’ performance was expected be high. The teachers would also need to sort out challenges facing them with a view of minimizing them to avoid the same affecting their students’ performance. The study recommended policy changes and retooling of teachers on their expectations in terms of work-life balance, their work planning and time management for performance of their students. Keywords: Work-life balance, time management, challenges, Academic Performance DOI: 10.7176/EJBM/15-8-04 Publication date: April 30 th 2023

Utility of Brief Illness Perception Questionnaire for Assessing the Acute Impact of COVID-19 Infection: A Psychometric Study

Background: The coronavirus disease-19 (COVID-19) pandemic has created mental health repercussions in the lives of many individuals. It is important to understand emergent perceptions of this illness among patients with a recent diagnosis of COVID-19. Due to its good psychometric properties, the brief illness perception questionnaire (BIPQ) has been widely used for various illnesses and in different languages. Its application in recently diagnosed COVID-19 patients is an area worth exploring in an Indian setting. Aim We aim to understand the patient’s perception of COVID-19 illness using the hindi adaptation of BIPQ and validate for its further use in a similar type of acute setting.Method This tool was customized by three subject experts for its application in recently diagnosed COVID-19 patients. A customized tool was circulated to nine subject matter specialists for the computation of the content validity index. The tool link was shared with patients. A total of 112 patients responded. Factor analysis and reliability analysis were also conducted.Result Item content validity index for all items in the BIPQ scale was in the acceptable range (value above 70%). Scale-content validity index/universal agreement was 88.8%. Bartlett’s test was significant (p < 0.001) and the Kaiser-Meier-Olkin measure of sampling adequacy was 0.777. The factor loading threshold was fixed at a value above 0.40. Eight Likert scale items of BIPQ based on factor analysis were regrouped in two. Items one, two, four, five, and eight were in group one, which depicted “concrete perception,” and items three, six, and seven were in group two which depicted “gestalt perception” of recently diagnosed COVID-19 patients. Cronbach’s alpha of the scale was found to be high at 0.808.Conclusion Results depicted a two-factor structure of BIPQ with satisfactory validity and reliability. We suggest regrouping of existing items of BIPQ into two domains, namely “concrete perception” and “gestalt perception” for recently diagnosed patients with COVID-19.