Usefulness of interactive video-based instruction on learning performance in relation to cognitive development of children with moderate intellectual disability

Abstract

The usefulness of information and communication technology has been witnessed around the globe with the occurrence of rapid changes in the field of education i.e. through the formal or informal way. For this, the researchers have assessed Interactive video-based instruction (IVBI) on (N = 95; males = 47 & females = 48 age range between 12 and 15 years) moderate intellectual disability children in Guwahati, Assam, India from three day-care rehabilitation centres. The main objective was to examine the effect of IVBI intervention (IIVBI & CIVBI) on academic performance in association with the cognitive development of children with moderate intellectual disability in a comfortable setting within working hours. The findings conclude that children in the CIVBI group performed more actively as compared to IIVBI and comparison group, and it was due to the involvement of video-based instruction that helped understand the topic more precisely and acts effectively for CIVBI children in an experimental setting.

Keywords

cognitive development collaborative learning individual learning intellectual disability interactive video-based instruction learning performance moderate intellectual disability

Introduction

Inclusive education is a platform that supports all children's learning, regardless of their ability, and encourages them to learn in the same school without any barriers or prejudice (UNICEF, 2016). It is a broad discipline that enables children with intellectual disabilities to make significant progress in improving their adaptive behaviour and cognitive abilities, allowing them to excel in academics and other important skills (Dessemontet et al., 2011). In the framework of inclusive education, thorough planning is required in the development of curriculum, specifically built classrooms, and the provision of adequate infrastructure (Sharma, 2018).

The educational requirements of children with disabilities cannot be met unless education for all is implemented properly and the process of isolation teaching is discontinued (Kumar, 2010). Notable initiatives have been conducted at the global levels where Goal 4 of the SDGs 2030 strictly emphasis on inclusiveness, equitable quality education, constant knowledge acquisition, and equal access to vocational training for vulnerable groups (Sustainable Development Goals, 2015) and Global Action of Disability (2015) took an important step towards ensuring the health, happiness, and human rights of people with disabilities. Similarly, the National Education Policy (2020) seeks to transform the Indian education system by guaranteeing fairness and inclusion through a diverse variety of educational options (curriculum, pedagogy, infrastructure, teaching-learning, and recreational activities).

Though in India many policies and organizations have been established to eradicate the problems but due to insufficient manpower, inadequate facilities, less number of special schools, behavioural attitudes, and lack of funds several initiatives remain only as a part of planning instead of actions as compared to Western and European countries. Researchers, policymakers, NGOs, and young scholars in developed countries are conducting numerous studies on special needs to develop effective solutions to address the problem. In social settings, people are organised into various categories with different behavioural problems. People with diverse disorders are looked down upon by community people and considered abnormal or slow learners. As witnessed by everyone there is a concept of special schools, day-care rehabilitation centres, and home-schooling specially designed for children with disabilities. But, separating the right to education from the children needs to be fostered into action and start providing education under the same roof without any barriers based on the rate of disabilities. That is why after thorough observation the researchers have planned to assess Interactive video-based instruction (IVBI) intervention in two day-care rehabilitation centres and one special school for training children with moderate intellectual disability in their cognitive developmental process in Assam, India.

The relevance of the present study refers to a method used in North East India to identify children with moderate intellectual disability in day-care rehabilitation centres who were subjected to interactive video-based intervention for learning various cognitive tasks. Due to the availability of rehabilitation centres with moderate intellectual disability populations for the experimental procedure, the current study is determined to be adaptable for performing in Assam. A recent research was done in Guwahati, Assam, India where most disabled children were neglected by community members due to their numerous symptoms, affecting the lives of children, particularly in their academic performance, daily living abilities, communication skills, and problem-solving skills. For this, a collaborative learning environment for children with disabilities should be built to teach various functional and adaptive skills for their growth (Plavnick et al., 2013).

However, technological innovation has touched every element of development, yet employing ICT facilities within the classroom, particularly for the disabled population, is quite restricted in Assam. During the trial phase, the researchers discovered few rehabilitation centres included ICT facilities for teaching social skills via video supported classroom (Barman & Jena, 2021). To evaluate the effects of IVBI sessions on the academic performance and cognitive development of a child with moderate intellectual disability, the researchers have to cover all necessary equipment such as; a camera, tripod, projection screen, speakers, mobile phone, and laptop for experimenting.

In regard, the researchers aim to investigate the effects of IIVBI and CIVBI on the learning performance of children with intellectual disabilities and their relationship with cognitive development in the experimental group and the comparison group.

Intellectual disability

Intellectual disability is a neurodevelopmental disorder characterised by deficits in both cognitive (problem-solving) and adaptive functioning (daily living skills), which are commonly associated with various disabilities (AAIDD User's Guide Work Group 2012; APA, 2015). Intellectual impairment may be classified into four categories based on abilities, capacities, and learning experiences such as; Mild, Moderate, Severe, and Profound, as well as activities for improving academic and functional skills are offered according to their IQ level (see Table 1).

Table 1.

Categorisation and types of intellectual disability.

S/N	Categories of intellectual disability	IQ level	Symptoms
1	Mild	55–69	Slow learners, average conceptual development, and moderate social interaction.
2	Moderate	36–54	Slow learners basically in understanding and communicating with others. They can do simple tasks like reading, writing, and counting skills.
3	Severe	20–35	Delays in development need proper supervision to accommodate and often required family support to do daily life skills within the social settings.
4	Profound	<20	They required close supervision of self-care activities, show an incomplete ability to communicate, inadequate physical movement, and proper associated medical conditions need to serve for creating sound living space like a normal child.

Types		Weaknesses
1	Autism spectrum disorder	It affects one’s actions, interactions, communication, and learning process
2	Fragile X syndrome	It is considered an inborn difficulty that predominantly affects males with some distinctive physical features
3	Down syndrome	Generally, mild-moderate intellectual disabilities come across this symptom with a common chromosomal abnormality that shows distinctive physical characteristics
4	Developmental delay syndrome	Individuals have delays in fine & gross motor skills, speech, language, thinking, and motor skills.
5	Prader-Willi syndrome	It is identified as a genetic disorder that causes obesity and shortness in height with some common symptoms such as; delayed puberty, excessive hunger, aggression, compulsive behavior, excess sleepiness, and small feet
6	Fetal alcohol spectrum disorder	It is the leading cause of intellectual disability in modern times including individuals with mild-moderate intellectual disability associated with various physical deformities.

Besides, several forms of impairments might be discovered or diagnosed when a child exhibits cynical conduct during the developing process. Intellectual disability is caused by genetic and chromosomal abnormalities, infection during pregnancy, and impairment in siblings. As a result, different symptoms of intellectual disability will differ depending on the child's level of disability, such as failure to meet cerebral standards, sitting, crawling, or walking slowly in comparison to other normal children, speaking problems, slow memory retention, showing childish behaviour, lack of curiosity, and learning difficulties. In addition, Brown et al. (2012) found that children with intellectual disabilities can provide valuable information during forensic interrogations, outperforming severe cognitive impairments.

Interactive Video-Based Instruction: A Hope of Educating Intellectual Disability

In simple words, IVBI is the process of choosing, recording, uploading, and evaluating the full content production scenario for the desired purpose again and over again. The effect of video-based learning in classrooms offers numerous benefits, including high student appreciation, precise illustrations compared to text-based presentations, and the ability to incorporate realistic presentations into practice (Avcioglu, 2013; Ayres & Langone, 2008). Similarly, embodied interactive video lectures can assist learners learn any task by providing various sorts of interactions functions during the learning process for longer retention (Hung & Chen, 2018).

Interactive video-based instruction (IVBI) offers users control over their experience through various tools and features, making it useful in various contexts like education, corporate training, customer care, and e-commerce. IVBI enhances personalization, engagement, conversion, and audience insight, making it a valuable tool in various industries. Further, Benkada & Moccozet (2017) study reveals that interactive films are an important part of the teaching and learning process as teachers use them to communicate or share course information with students, while students utilise them to complete assessment work as required. In contrast, an interactive digital art platform allows an individual with intellectual disabilities to identify their creativity, hidden talents, work engagement, and active participation through various provided situations (Albrecht et al., 2021).

Furthermore, IVBI is a method of giving significant information on a certain topic to learners via video mode with clear suggestions for attaining longer retention, memory, perfection, and getting precise knowledge for learning objectives. In contrast, Schwan & Riempp (2004) discovered that participants in an interactive condition participated more actively than non-interactive users to accomplish the knot-tying task because they had more opportunities to stop, repeat, and reverse the video. IVBI approach assists learners in understanding the topic more clearly because it incorporates both audio-visual facilities for better learning. Children with Special Educational Needs and Disabilities (SEND) can benefit from interactive apps provided on touch-screen tablets because they can enable high levels of engagement with the learning task and foster an inclusive learning environment (Pitchford et al., 2018). As a result, the student’s active participation, growing interest, and satisfaction level increase with the use of a video-based learning environment (Tuma, 2021).

Developing Cognition of Intellectual Disability: A Comprehending Issue

Cognitive development is the process of carrying out an activity that is grounded in a person's theoretical and practical understanding. It is the result of doing activities such as remembering, problem-solving, critical thinking, logical reasoning, abstract reasoning, retention, memorisation, and fact identification. Many studies have found that the usage of technology was the most persistent factor in the development of an individual's cognitive development skills in every way. According to Afify (2020), interactive digital video-based learning (lengthy, medium & short movies) can help learners reduce cognitive load and attain recall ability. However, in both children with and without IDD, fine and gross motor development are more closely linked to cognitive and language development (Houwen et al., 2016).

Children with impairments require cognitive skill development, necessitating adequate training and frequent practices in daycare rehabilitation facilities to encourage and prepare them to tackle daily problems. Edpuzzle, an online video learning platform, can enhance critical thinking skills in both learners and instructors by offering editing features for active learning videos tailored to specific class needs (Pulukuri & Abrams, 2020). Similarly, consistent use of computer games can help children with intellectual disability enhance their academic learning and cognitive abilities (Bell et al., 2013). Likewise, the storytelling technique was useful for assisting children with impairments of various ages in adjusting to their social systems as well as improving their imagination capacity to think logically (Chan, 2019). The study indicates that phonological information processing is a significant factor contributing to cognitive impairment in individuals with moderate or borderline intellectual disabilities (Schuchardt et al., 2010).

Furthermore, academics, psychologists, politicians, and curriculum designers employ advanced technology to analyse or appreciate the scholastic, emotional, and psychological benefits of children with impairments in modern times. Earlier research findings indicate that using video-based instruction (VBI) through video presentations significantly enhances cognitive learning in students with intellectual disabilities (Moemennasab et al., 2002). Additionally, (Kirk et al., 2015) study revealed a strong correlation between attention and working memory, fundamental cognition processes, and the academic achievements, language skills, and behavioral development of children with intellectual disabilities. Likewise, the edutainment system had a significant influence on children with intellectual disabilities in terms of cognitive development, increased motivational levels, and physical activity in the classrooms (Dandashi et al., 2015). Accordingly, emotion recognition and interpretation skills are more crucial for children with mild to borderline intellectual impairments in predicting social processing than working memory and inhibitory skills (Van Nieuwenhuijzen & Vriens, 2012).

The main objective of the study includes (1) To study the effects of IIVBI and CIVBI on the learning performance of intellectual disability children over the comparison group. (2) To inter-relate the effect of IIVBI and CIVBI on the cognitive development of experimental group children with those in the comparison group.

The demographic structure of the study

The demographic structure of the present study relies on the availability of moderate intellectual disability children in three selected rehabilitation centres in Guwahati, Assam, India. The majority of participants included were concerning various disability issues like functionality skills and adaptive skills.

The rise of technological advancement has led to various opportunities for growth and development in all spheres of life. Especially, the population with disabilities has more vulnerable conditions in dealing with these rapid changes. Though many quantitative and qualitative studies were undertaken by different researchers from various countries but no such studies have been conducted yet on moderate intellectual disability children’s cognitive development using IVBI intervention in Assam, India. That is why; the present study was undertaken by the researchers to fill the gap by imposing new strategies for developing cognitive skill development among moderate intellectual disability population.

For this, the researchers have minutely observed the need and interest of the requirements that were necessary to be utilised in the field of studying the difficulties of the children associated with their cognitive development. Therefore to meet the challenges in everyday life the researcher’s present initiative would add some effective effort in dealing with the situation based on different circumstances.

Method

Settings

The setting for the recent work was arranged in three rehabilitation centres in Guwahati, Assam i;e Uttaran special school (n=32) children with moderate intellectual disability were selected for experimental group I where IIVBI intervention was provided, Ashadeep day-care rehabilitation (n=30) children were assigned to experimental group II were CIVBI intervention was provided, and Essha foundation (n=33) children were assigned to conventional group were lecture cum discussion approach was formulated.

In the entire process of experimentation, all the teacher trainers, working interns and other staff cooperated actively throughout the working six months. All the selected centres were located in a comfortable environment with all facilities such as providing school buses, following flexible routines, offering lunch breaks, organising co-curricular activities, and regular doctor’s visit. The selected centres follow some effective goals instead of a fixed curriculum which allows flexibility for a child to engage in their interested activity and learn accordingly. An emphasis on personality development was also witnessed as many opportunity doors were opened through various activities like sports, painting, dancing, teamwork, and employment skills. Hence, for the need of the study, moderate intellectual disability children were involved in all the training programs.

Participants

Before the instruction, the researchers encounter more than 200 children in the three selected rehabilitation centres situated in Guwahati, Assam, India, who were admitted for their skill development in all areas. For the study, the researchers administered a Diagnostic Statistical Manual test to all of the children and determined that 30 were mild, 95 were moderate, 41 were profound, and 34 were severe. In an open observation after DSM testing, the researcher identified children's disability symptoms, language development, and functionality skills based on their levels of three domains such as conceptual, social, and practical.

It was observed that mild children were having improved skills in all the domains, moderate children were showing slow improvement, severe children were having only limited improved skills, and profound children showed no sign of improvement. Finally, the researchers have decided to choose (n=95) moderate intellectual disability children for the present experimentation. It means, from rehabilitation centre I (n=32) children were documented where (males=12 aged 12 to 14, and females=20 aged 12.5 to 14), and from rehabilitation centre II (n=30; male=17, ages 13 to 14, and female=13, ages 13.5 to 14). Furthermore, rehabilitation centre III (n=33; male=18, ages ranging from 12.5 to 15 and females=15, ages ranged 12 to 14.5) children were assigned to the comparison group for traditional treatment.

After sample selection, the researchers regularly visited these rehabilitation centres to know the present status of the children's disability levels, developmental skills, and functionality skills respectively. As per observation, the researchers have pointed out that, mild children face problems in intellectual presentation with undeveloped societal relations. In the case of moderate children's academic skills are slowly developed with limited social and communication skills. In addition, severe children showed limited conceptual skills and require support for completing DLS activities, whereas, profound students learn new abilities by interacting with items with inadequate comprehension. As a result, the researcher selected children with moderate intellectual disability for the current study based on their average developed functioning skills.

Design

A quasi-experimental design followed by non-randomization and selective manipulation techniques was used for preparing the design to examine the effect of IVBI on learning performance to cognitive development in children with moderate intellectual disability. Accordingly, the participants were selected using DSM testing, regular observation, instrumentation, and recorded data from the rehabilitation centres. In addition, the participant’s ages, IQ levels, the status of their disability, and learning habits were given priority before selecting rehabilitation centres and assigning children to the experimental and comparison groups. After the selection (N=95) children with moderate intellectual disability the researchers decided to divide the children into three groups (n=32) children were allocated to experimental group I, while (n=30) children were assigned to experimental group II, and (n=33) children were assigned to comparison group for conventional group (see Table 2).

Table 2.

Design of the study.

Groups	Test I	Interventions	Test II
Experimental group I (N = 32)	Intelligence Test Pre-Test Cognitive development scale	Individual interactive video-based instruction (IIVBI)	Post-Test Cognitive development scale
Experimental group II (N = 30)	Intelligence Test Pre-Test Cognitive development scale	Collaborative interactive video-based instruction (CIVBI)	Post-Test Cognitive development scale
Comparison group (N = 33)	Intelligence Test Pre-Test Cognitive development scale	Lectured cum Discussion method	Post-Test Cognitive development scale

The study consisted of 27 weeks of training phase through IVBI (IIVBI & CIVBI) during the intervention and post-experimentation period. Besides, experimental group I children with moderate intellectual disability were taught using individual interactive video-based instruction (IIVBI), whereas experimental group II children were taught using collaborative interactive video-based education (CIVBI), and comparison group children learn through a traditional lecture cum discussion approach. After 6 months of instruction, the performance of the children with moderate intellectual disability was assessed through an achievement test and a cognitive development scale correspondingly. The post-test scores were compared with pre-test scores to minimize the extraneous variable effect that was identified during the experimentation process.

Instrumentation

Achievement Test

Following the normal criteria, syllabus, curriculum, and targeted goals used in rehabilitation centres, an achievement test was prepared for children with moderate intellectual disability. In rehabilitation centre I (IIVBI), goals like (language development, personality development, problem-solving, social skills, and co-curricular activities) followed by rehabilitation centre II (CIVBI), including targeted goals (academic achievement, social skills, co-curricular activities, functionality skills, and personality development) were recorded by the researchers.

However, teachers in rehabilitation centre III use NCERT books to teach numbers, the alphabet, general knowledge, and other subjects with regular exercise, speech therapy, and doctor visits. To develop the accomplishment test questionnaire, the researchers meticulously followed five competencies such as; communication skills, functionality competency, problem-solving skills, daily living skills, and life skills activity (see Table 3).

Table 3.

Shows details of five competencies with areas of learning performance included under the achievement test.

Sl No.		Learning performance	Areas of learning performance
1	C O M P E T E N C I E S	Communication skills	Reading fluency
			Writing alphabets
			Listening stories
			Clarity in speech
			Greeting politely
2		Functionality competency	Using transportation
			Visiting grocery stores
			Self-independent
			Helping others
			Respecting others
3		Problem-Solving competency	Simple calculation
			Tracing exercise
			Calendar activity
			Teamwork
			General knowledge
4		Daily Living Skills	Following morning Routine
			Self-grooming
			Regular exercises
			Personal hygiene
			Meditation
5		Life Skills Activity	Personality development
			Self-confidence
			Hobby practices
			Leadership training
			Decision making

The achievement test comprises 20 multiple-choice items with three possibilities and one mark for each right response, 10 very short type items with one mark for a correct response, and 10 short type items with two marks for a correct response. The included items were; tracing and writing alphabets, simple calculations, calendar activity, reading and writing skills, learning time management skills, personal hygiene, daily routines, meditation, and regular exercise.

Cognitive Development Scale

The cognitive development scale consists of three factors viz; problem-solving skills, logical reasoning skills, and language skills followed by five sub-categories under each area. A problem-solving skill includes (creativity, communication, decision-making, active listening, and group work), logical reasoning skills includes (inductive reasoning, abstract reasoning, verbal reasoning, spatial reasoning, and deductive reasoning), and language skills include (listening, speaking, reading, writing, and practice) (see Table 4).

Table 4.

Areas of cognitive development.

Areas	Sl.No	Dimensions	Areas of development
Cognitive Development	1	Problem-solving skills	Creativity
			Communication
			Decision making
			Active listening
	2	Logical reasoning skills	Group work
			Inductive reasoning
			Deductive reasoning
			Verbal reasoning
			Spatial reasoning
	3	Language skills	Abstract reasoning
			Listening
			Speaking
			Reading
			Writing
			Practice

A total of 30 items were prepared based on the selected three sub-categories and accordingly assigned the activity worksheets. Likewise, the included items were simple calculations, alphabet tracing, solving jumble words, calendar activity, colour and name the picture, dot joining, fill in the blanks, fruit tracing, identifying colour names, inserting missing alphabets, match the letters, matching task, complete missing letters, insert missing numbers, number tracing, pattern tracing, picture recognition, writing seasons names, shapes tracing, naming solar systems, doing sum as activity, testing G.K, tick the correct response, tick the odd one out, time telling, vegetables tracing, writing months names, what comes next, word formation and solving word problems.

Phases of Data Collection

Phase I: Individual interactive video-based instruction (IIVBI)

Self-learning is an effective strategy that encourages individuals to acquire new abilities, finish tasks, boost output, and solves issues regularly (Hughes, 1991). The main objective of individual learning is to develop self-confidence, achieve specific goals, develop self-learning abilities, and also to adopt independent skills for sustainability. IIVBI fosters an open environment for students to learn in their interests, while setting clear goals ensures smooth progress in any chosen activity. Moreover, Evmenova et al. (2017) discovered that students did better learning and understanding with modified and interactive video clips.

In the present work before experimenting, the researchers obtained an authorization letter from the university's higher authority for gathering data. Also, the researchers have visited the selected centres regularly for a better understanding of the environment. For this, a short duration of training on interactive video-based intervention was provided to the participants (n=32) by showcasing the video tutorials (eg; simple calculations). The duration of each recorded video last for 5-10 mins with a step-by-step demonstration. The centre provided a separate room for experimenting where participants' pre-test intervention was administered individually with the help of an achievement test and cognitive development scale. Similarly, the recorded videos were played using a laptop supported by a bluetooth speaker for better sound clarity. The entire working session was recorded by the assistant helper using a tripod and mobile phone.

In this way, each video shown to an individual was followed by a questionnaire and practiced worksheet for effective memorisation and retention capacity. The participants were allotted 10-15 mins to complete the task and submit the questionnaire. In regards, Suharja et al. (2019) findings indicated that regular usage of interactive movies can improve brushing skills among moderate intellectual disability children. In context, Riyanto & Gunarhadi (2017) results show that PowerPoint's interactive learning multimedia helps students with arithmetic learning disabilities.

Phase II: Collaborative interactive video-based instruction (CIVBI)

Collaborative learning fosters a group or teamwork environment in which any task may be accomplished (Bigby et al., 2013). It is a process of teaching and learning where students performed in a group to explore a significant assignment which provides a positive output. Additionally, (Burns et al., 2014) demonstrates that with a well-structured timetable, collaborative learning is a successful means of engaging kids in learning. According to the study, students with visual impairments (SIVs) were able to develop higher order thinking skills through collaborative learning using diagrams and models (Sharma & Chunawala, 2015).

Collaborative learning fosters an engaging environment in which people with disabilities may enhance their interpersonal skills (Joiner 2004). Collaborative interactive video-based instruction (CIVBI) has played a significant role in making the teaching-learning process more interesting by including both video-audio formats for children with intellectual disability. The main purpose of CIVBI is to develop group activities for active participation and knowledge sharing. It provides a chance of reducing stress, insecurity, hesitation, and uncomfortness while involved in any activity. CIVBI also helps to stimulate learners’ mental abilities with other aspects like assimilation, accommodation, and association within the learning environment. This way the children will understand why teamwork is important, how coordination can work, and when cooperation is required for the improvement of various skills. It was resulted that collaborative digital game-based learning (DGBL) and efficient instructional video use can considerably increase motivation in reducing both internal and extrinsic cognitive load, followed by learning behavioural patterns among students (Liao et al., 2019).

Accordingly, the researchers have assigned centre II children (n=30) to the CIVBI group for experimentation. For this, the moderate intellectual disability children were divided into six groups with five members each of different ages. Without training, a pre-test intervention was conducted to measure the children's prior knowledge using an achievement test and cognitive development scale. In addition, a set of achievement tests and cognitive development questionnaires were prepared including different items based on the participant's improvement and asked to complete it within 10-15 minutes.

For the documentation of an entire intervention, some teacher-educators and working interns help out the researchers effectively. The children received regular video intervention after finishing the pre-test instructions followed by previously filmed videos and printed practice worksheets. Similarly, a post-test was delivered to the same group of children with the same questionnaire to compare scores with the pre-test and judge their improvements. Furthermore, Roldán-Álvarez et al. (2021) studies indicate that using video self modelling to teach job related skills to students with intellectual disabilities was beneficial. Thus, collaborative learning is advantageous for kids with disabilities when it comes to learning particular actions associated with skill improvement (Wishart et al., 2007).

Phase III: Conventional approach

Traditional treatment was provided to the comparison group children (n=33) with moderate intellectual disability by introducing activities like; book reading, traditional lectures, and demonstration cum discussion technique. Here, without any prior teaching, participants were distributed with printed questionnaires for the pre-test session and were asked to complete the task within 10-15 minutes. Likewise, after completion of pre-test session the intervention classes were delivered in an open hall for 15-20 minutes on daily basis where the researchers introduce different types of knowledge based on child’s cognitive development. As a result, they were exposed only to printed worksheets, printed materials, and narrative techniques for understanding any topics. Similarly, after proper preparation, the same children encountered post-test sessions with the same questionnaires to see their performance. However, the researchers have gathered all pre-test and post-test response sheets, as well as additional worksheets from both the experimental and conventional groups for further approach.

Analysis and Results Interpretation

The researchers have assumed that IIVBI and CIVBI training children with moderate intellectual disability have performed better than the comparison group in their specified learning goals that were set by the rehabilitation centres.

The pre-test mean performance of IIVBI group (n=32) was (M=5.84 & SD=1.609) which is lowest over the pre-test mean of CIVBI (n=30, M=6.77 & SD=1.223) and pre-test mean of the comparison group (N=33, M=6.79 & SD=1.244). In the case of a post-test mean of CIVBI (N=30 M=36.40 & SD=5.014), that is better than the post-test mean of IIVBI (N=32 M=27.25 & SD= 1.646) and post-test mean of the comparison group (n=33, M=10.58 & SD=1.347) (see Table 5).

Table 5.

Descriptive statistic of pre-test post-test and mean score and SD of IIVBI, CIVBI, and comparison.

Group	Interventions	Pre-Test		Post-Test
Group	Interventions	Mean	SD	Mean	SD
Experimental Group I	IIVBI	5.84	1.609	27.25	1.646
Experimental Group II	CIVBI	6.77	1.223	36.40	5.014
Comparison Group	Conventional	6.79	1.244	10.58	1.347

In addition, descriptive analysis resulted that the IVBI has a significant effect on the comparison group. But, while constructing collaborative groups with interactive video-based instruction (CIVBI) training children with moderate intellectual disability performed better than the IIVBI. However, IIVBI children with moderate intellectual disability were not able to share their opinion, answer and discuss their problems with their peer group to achieve their learning goals constructively. That is why; it was found that among all three groups, CIVBI children with moderate intellectual disability performed much better over IIVBI and comparison groups.

As predicted the experimental group of children using CIVBI (M=36.40) was better over the pre-test and post-test mean of the other two groups. The estimated marginal mean of a dependent variable post-test mean of IIVBI and CIVBI (M=27.469 & 36.293) was better than the post-test mean of 10.461 of the comparison group. The post-test mean difference between IIVBI and CIVBI was (-8.824 p< .05), IIVBI and Comparison group (17.007 p< .05) (see Table 6).

Table 6.

Estimated post-test mean of IIVBI, CIVBI, and comparison group.

Group	Mean	Std. Error	95% Confidence Interval
Group	Mean	Std. Error	Lower Bound	Upper Bound
IIVBI	27.469^a	.559	26.358	28.579
CIVBI	36.293^a	.562	35.176	37.410
Comparative group	10.461^a	.537	9.394	11.528

^aCovariates appearing in the model are evaluated at the following values: pretest = 6.46.

The adjusted Bonferroni multiple comparisons between CIVBI and IIVBI at the post-test level was (8.824 p< .05) and the mean difference between CIVBI and the comparison group (25.832 p< .05) was significant at .05 level. However, the alternative hypothesis was accepted and there exists a significant effect of IIVBI training children with moderate intellectual disability in association with those in the comparison group (see Table 7).

Table 7.

Bonferroni multiple comparisons of the post-test of IIVBI, CIVBI, and comparison group.

(I) Group	(J) group	Mean Difference (I-J)	Std. Error	Sig.^b	95% Confidence Interval for Difference^b
(I) Group	(J) group	Mean Difference (I-J)	Std. Error	Sig.^b	Lower Bound	Upper Bound
IIVBI	CIVBI	−8.824^*	.806	.000	−10.789	−6.859
IIVBI	Comparative Group	17.007^*	.789	.000	15.083	18.932
CIVBI	IIVBI	8.824^*	.806	.000	6.859	10.789
CIVBI	Comparative Group	25.832^*	.771	.000	23.952	27.712
Comparative Group	IIVBI	−17.007^*	.789	.000	−18.932	−15.083
Comparative Group	CIVBI	−25.832^*	.771	.000	−27.712	−23.952

Based on estimated marginal means

^aThe mean difference is significant at the .05 level.

^bAdjustment for multiple comparisons: Bonferroni.

Model 1 Learning performance of IIVBI, CIVBI, and comparison with cognitive development (Problem-solving skills)

Figure 1 depicts the standard path coefficient and fit indices of IIVBI and CIVBI learning performance and comparison with cognitive growth (problem-solving skills) of children with moderate intellectual disability. The fit indices indicated a strong data fit while χ2= 165.749 DF= 132 was significant at .05 level. Regarding the structural path of PIVBI, the learning performance has a significant positive relationship with the factors of problem-solving skills (see Figure 1).

Here, creativity (R²=.25 Beta= .06 p< .05), communication (R²=.97 Beta= .94 p< .05), decision making (R²=.84 Beta= .71 p< .05), active listening (R²= -.19 Beta = .04 p< .05), and group work (R2=-.50 Beta=.33 p< .05) has significant relationship with the performance. Similarly, PCIVBI has a significant relationship with the problem-solving skills of children with a moderate intellectual disability. All the latent variables such as creativity (R²=.59 Beta=.34 p< .05), communication (R²=-.73 Beta =.54 p< .05), decision-making (R²=.61 Beta= .37), active listening (R²=94 Beta=.89), and group work (R²=.9 Beta=.48) has a significant positive relationship with the performance of PCIVBI. As compared to PIIVBI and PCIVBI - PCG has no positive relationship with all the factors of problem-solving skills of cognitive development.

All the latent variables such as creativity (R²=.66 Beta=.44 p< .05), communication (R²=-.73 Beta =.54 p< .05), decision making (R²=.60 Beta =.36 p< .05), active listening (R²=-.37 Beta= .14 p< .05), and group work (R²=1.19 Beta=.03 p< .05) has no significant relationship with the latent variables. So far model fit summary was concerned, the CMIN/Df in the default model was 1.256 where CMIN= 165.749 and DF=132 was significant because the value lying in between 1& 3 indicated a good fit (Kline, 2005).

The baseline comparison in the default model, CFI=.752 P< .05 indicated better fit (Hu & Bentler, 1999) while NFI =.460, RFI=.301, IFI=.807, TLI=.678 showing the significant relationship. In parsimony adjusted, PCFI=.580 while PNFI=.355 and PRATIO=.772 indicated a good fit. In the default model, NCP=33.749 p< .05 and the sample size is fit for the model while LO 90= 4.919, HI 90= 70.733. The FMIN in the default model was = 5.180 where F0= 1.055, LO 90=.154, HI 90=2.210.

The RMSEA .070 was acceptable while LO 90= .034, HI 90= .129, and PCLOSE=.097 has significant. So far the quality statistical model of the data sample used was concerned, the AIC=279.749 and BCC=446.364 were found significant (Akaike, 1987). In the default model, ECVI =8.742 represented a better result because the ECVI value was more than 80% and nearly equal to 1 where LO 90= 7.841, HI90=9.898, and MECVI=13.949. In addition, the Hoelter value was at .05 level= 31 and.01 level= 34. So the model was fit and provided the appropriate results (West et al., 2012).

Model 2 Learning performance of IIVBI, CIVBI, and comparison with cognitive development (Logical reasoning skills)

Figure 2 demonstrates the good fit of data with the cognitive development (logical reasoning skills) of children with moderate intellectual disability, indicating a significant correlation between learning performance and cognitive development. The fit indices suggested a good fit of data, where χ2= 165.749 DF= 132 was significant at .05 level.

Regarding the structural path of PIVBI, the factors of logical reasoning skills and performance have a significant relationship while inductive reasoning (R²=.26 Beta= .07 p< .05), abstract thinking (R²= -.58 Beta= .78 p< .05), verbal reasoning (R²=.72 Beta= .52 p< .05), spatial reasoning (R²= -.16 Beta = .02 p< .05), and deductive reasoning (R²=-.62 Beta=.39 p< .05).

Similarly, PCIVBI has a significant relationship with the logical reasoning skills of children with moderate intellectual disability, while all the latent variables such as; inductive reasoning (R²= -.66 Beta=.44 p< .05), abstract thinking (R²=-.68 Beta =.47 p< .05), verbal reasoning (R²=.86 Beta= .74 p< .05), spatial reasoning (R²=.50 Beta=.25 p< .05), and deductive reasoning (R²=.60 Beta=.36 p<. 05) has a significant positive relationship with PCIVBI (see Figure 2).

As compared to PIIVBI and PCIVBI – the performance of PCG has no positive relationship with all the factors of logical reasoning skills of cognitive development. All the latent variables such as inductive reasoning (R²=.91 Beta=.82), abstract thinking2 (R²=.51 Beta =.38 p< .05), verbal reasoning (R2=.30 Beta =.09 p< .05), spatial reasoning (R²=-.30 Beta= .09 p< .05), and deductive reasoning (R²=26 Beta=.08) has no significant relationship with the latent variables.

So far model fit summary was concerned the CMIN/Df in the default model was 1.645 where CMIN= 217.103 and DF=132 were significant because the value lying between 1 & 3 indicated a good fit (Kline, 2005). The baseline comparison in the default model, CFI=.428 P< .05 indicated better fit (Hu & Bentler, 1999) while NFI delta1=.321, RFI rho1=.121, IFI delta2=.547, TLI rho2=.259. In parsimony adjusted, the PCFI=.331 while PNFI=.248 PRATIO=.772 indicated a good fit. In the default model NCP=85.103 p< .05 and the sample size was fit for the model while LO 90= 48.565, HI 90= 129.543.

The FMIN in the default model was = 6.784 where F0= 2.659, LO 90=1.518, HI 90=4.048. The RMSEA was .142 acceptable while LO 90= .107, HI 90= .175, and PCLOSE=.000 was significant. So far the quality statistical model of the data sample used is concerned with AIC=331.103 and BCC=497.719 (Akaike, 1987). In the default model, ECVI =10.347 represented a better result because the ECVI value was more than 80% and nearly equal to 1 where LO 90= 9.205, HI 90=11.736, and MECVI=15.554 (West et al., 2012).

Hoelter value was at .05= 24 at .01= 26. So, the default model was fit and provided the appropriate results. The performance of the IIVBI and CIVBI training children with moderate intellectual disability has a significant positive relationship with logical reasoning skills (inductive reasoning, abstract reasoning, verbal reasoning, spatial reasoning, and deductive reasoning) and a negative relationship with problem-solving skills (inductive reasoning, abstract reasoning, verbal reasoning, spatial reasoning, and deductive reasoning) of the comparison group.

Model 3 Learning performance of IIVBI, CIVBI, and comparison with cognitive development (Language skills)

Figure 3 illustrates the standard path coefficient and fit indices of learning performance of IIVBI, CIVBI, and comparison group with cognitive development (language skills) of children with moderate intellectual disability. The fit indices suggested a good fit of data, where the χ2 = 190.180 DF= 132 was significant at the .01 level. The structural path of PIVBI performance has a significant relationship with the factors of language skills. While listening (R²=.13 Beta= .02 p< .05), speaking (R²=-.85 Beta= .73 p< .05), reading (R²=.88 Beta= .78 p< .05), writing (R²= -.19 Beta = .04 p< .5), and practising (R²=-.56 Beta=.32 p< .05) has significant relationship with PIVBI (see Figure 3).

In addition, the performance PCIVBI has a significant relationship with the language skills of cognitive development while all the latent variables such as listening (R²=.72 Beta=.52 p<.05), speaking (R²=-.88 Beta =.78 p<.05), reading (R²=.55 Beta= .30), writing (R²=66 Beta=.44 p< .05), and practicing (R²=.46 Beta=.21) has a significant positive relationship.

As compared to PIIVBI and PCIVBI- PCG has no positive relationship with the factors of cognitive development (language skills). All the latent variables such as listening (R²=-.91 Beta=.82 p<. 05), speaking (R²=-.61 Beta =.38 p< .05), reading (R²=.30 Beta =.09 p< .05), writing (R²=-.30 Beta= .09 p< .05), and practising (R²=1.28 Beta=.08 p< .05) has no significant relationship with the latent variables. So far model fit summary was concerned the CMIN/Df in the default model was 1.441 where CMIN= 190.180 and DF=132 was significant because the value lying between 1 & 3 indicated a good fit (Kline, 2005).

The baseline comparison in the default model, CFI=.550 P<.05 indicated better fit (Hu & Bentler, 1999) while NFI delta1=.367, RFI rho1=.179, IFI delta2=.654, TLI rho2=.417. In parsimony adjusted, the PCFI=.422 while PNFI=.283. PRATIO=.772 indicated a good fit. In the default model, the NCP=58.180 p< .05, and the sample size were fit for the model while LO 90= 25.474, and HI 90= 98.895.

The FMIN in the default model was 5.943 where F0= 1.818, LO 90=.796, HI 90=3.09. The RMSEA was .117 accepted while LO 90= .78, HI 90= .153, and PCLOSE=.006. So far the quality statistical model of the data sample used was concerned, AIC=304.180 and BCC=470.796 (Akaike, 1987) were significant. The default model of ECVI =9.506 represented a better result because the ECVI value was more than 80% and nearly equal to 1 where LO 90= 8.484, HI 90=10.778, and MECVI=14.712. Hoelter value was at .05= 27 and at .01= 30, and the model was fit and provided the appropriate results (West et al., 2012).

However, it has resulted that the performance of IIVBI and CIVBI training children with moderate intellectual disability has a significant positive relationship with language skills (learning, speaking, reading, writing, and practice) and has a negative relationship with the language skills of a comparison group.

Finally, after testing all three models of cognitive development, the researchers have drawn an inference that the performance of IIVBI and CIVBI training children with moderate intellectual disability has a significant positive relationship with problem-solving skills, logical reasoning skills, and language skills; and also has a negative relationship with a comparison group.

Discussion

It was found that cognitive development was significantly correlates with IIVBI and CIVBI training for children with moderate intellectual disability, with independent variables like problem-solving, logical reasoning, and language skills directly influencing learning performance compared to the conventional group (Agran et al., 2002; Anderson & Kazantzis, 2008; Burton et al., 2013; Jenni et al., 2014; Kellems et al., 2020).

The researchers have revealed that children from centre I (IIVBI) participated actively in the experimental session that took place during working hours. In addition, children were exposed to a video learning environment for which the provided task becomes easier for them to complete. But some children face trouble in finishing the assignment because they are afraid to speak up and avoid face-to-face interaction. However, with proper intervention via IVBI format, the activity becomes simpler to understand and solve without any assistance. But some take longer to complete tasks due to issues like understating capacity, language barriers, and learning difficulties.

Similarly, the children from centre II (CIVBI) participated more actively as compared to IIVBI and the comparison group. Accordingly, the children were divided into groups to perform the task during the intervention process. The prepared worksheets along with recorded videos were encountered by the children which creates curiosity among them to learn. The children's performance was extremely good due to improved social skills training, personality development, proper skills training, activity-based learning, and facilitated programs.

In the case of centre III (comparison group), the researchers observed that the children with moderate intellectual disability showed least interest when performing the assignment during experimental phase, which was related to the lack of a video-supported learning environment instead of merely a lecture and discussion method for understanding and completing the given exercise. It was reported that more additional assistance was required followed by extra time allotment in the conventional group for completing the given task. The barriers to those delays predict age differences, poor social skills, and language problems. Interactive computer play can enhance the participation of children with sensori-motor disorders by reducing deficits, improving functional capacity, and ultimately increasing their overall participation in society (Sandlund et al., 2009).

VBI refers to the learning process that includes instructional videos, mini-lectures, video modeling, tutorials, and short stories which are associated with a specific syllabus, course content, learning materials, and extra information (Bereznak et al., 2012; Chan, 2019; Yakubova et al., 2019). In addition, Choi & Johnson (2005) reported that the VBI was effective in enhancing learners’ retention and motivation levels as compared to traditional text-based instruction. Similarly, Söderström et al. (2021) study emphasises that the regular use of assistive technology among young adults with intellectual developmental disabilities can enhance their participation in daily activities and boost their self-determination. The application of Spherical Video-based Virtual Reality (SVVR) technology in the classroom improves student learning results, problem-solving skills, and motivation to learn new things (Wu et al., 2021).

The rising use of technology can be witnessed by the increasing quantity of work undertaken by researchers using technology-based instruction for people with disabilities (Goldsmith & LeBlanc, 2004). Digital technology, including smartphones, social media platforms, and internet connectivity, has become a crucial asset for the young generation, enabling them to sustain everyday life and practices, both in India and globally (Iivari et al., 2020). The research revealed that video modelling was successful at encouraging generalisation, inspiring students, and drawing attention to maintaining qualities as compared to vivo modelling (Charlop-Christy et al., 2000).

In India, many policies and guidelines were followed in ensuring inclusive facilities (Singh, 2016), but the implementation of these policies faces numerous challenges due to a lack of awareness, inadequate funds, trained personnel, availability of schools, and accessibility (Barua et al., 2017). It was observed that moderate intellectual disability children in both IIVBI and CIVBI learning environments established a positive relationship with cognitive development training in learning various activities using video-based instruction (Lazakidou & Retalis, 2010; Moemennasab et al., 2002; Sigman & McGovern, 2005). But the children in the comparison group show a negative relationship throughout the intervention and this was due to the absence of video-based instruction. Video-based instruction offers the improved prospect to acquire better academic and functional skills, especially for students with disabilities (Contreras et al., 2019; Wilkes-Gillan & Joosten, 2016).

In addition, many studies supported the use of technology to be the most enduring aspect in the growth of an individual's cognitive development talents in every way, which was aided by (Cihak et al., 2009; Hong et al., 2016; Kellems et al., 2020). Likewise, the present work also took an effort to highlight the effectiveness of using IVBI intervention for cognitive improvement among children with moderate intellectual disabilities. Similarly, (Chan 2019; Khanna & Kareem 2021) discovered that people with impairments of all ages can adjust easily to their social environments and develop their creative ability through the storytelling method. The finding reveals that Theory of Mind (ToM) is significantly higher in inclusive classrooms compared to special classrooms for moderate intellectually disabled children (Smogorzewska et al., 2019).

In general, earlier researchers (Contreras et al., 2018; Dekker et al., 2002; Prater et al., 2011) found that the introduction of video games combined with teacher interaction may help children with impairments develop their physical, cognitive, and emotional skills. Similarly, self-control and working memory both contribute to the improvement of social skills in moderate intellectual disability patients (Dučić et al., 2018). Moreover, CBVI intervention increases the amount of instruction given to pupils on how to interpret signs and react independently in grocery stores (Mechling et al., 2002). Likewise, students' performance in an interactive video education environment improved significantly more than in other settings as a result of exposure to learning materials in video formats (Zhang et al., 2006). Due to the involvement of video learning children with different disabilities can simultaneously use their mental abilities in adjusting to the new learning situation (Bellini et al., 2007; Burton et al., 2013).

Video-based training helped develop functional skills and problem-solving skills for both with and without disabilities children’s (Ayers & Langone, 2008). In some cases, problem-solving techniques are a successful way to treat mental depression in people with moderate intellectual disability (Anderson & Kazantzis, 2008). A study conducted in Ireland (O’Reilly et al., 2002) examined that the problem-solving method works to be a powerful technique for teaching various cognitive skills to students with intellectual disabilities.

Accordingly,Agnew & Powell (2004) examined that children with mild or moderate intellectual disabilities can provide more specific information than mainstream age groups using ICT facilities. It was revealed that using computer-based instruction methods followed by observation, collaboration, and semi-structured guidance increases students’ problem-solving skills (Lazakidou & Retalis, 2010).

Similarly, important cognitive abilities like attention and working memory are significantly linked to academic success, linguistic development, and behavioral stability in children with intellectual disabilities (Kirk et al., 2015). As a result, Ahn & Hwang's (2018) findings review that cognitive strategies are useful for recovering adaptive behaviour related to neurodevelopment disorders. An experimental study suggests an effective further intervention should be included in improving motor, cognitive, and social outcomes in people with intellectual and developmental disabilities using the VBI format (Houwen et al., 2016).

Likewise, Dandashi et al. (2015) examined that the Edutainment system significantly influenced the cognitive development, motivation, and physical activity levels of children with intellectual disabilities. It was noted that many studies supported the use of technology to be the most enduring aspect in the development of an individual’s cognitive development skills in all respect (Cihak et al., 2009; Hong et al., 2016; Kellems et al., 2020).

The entire process of VBI includes support in remembering, retaining, memorizing, problem-solving, logical reasoning, and abstract thinking which automatically helps in cognitive development (Dandashi et al., 2015; Goharpey et al., 2013). Due to the involvement of video learning children with different disabilities can simultaneously use their mental abilities in adjusting to the new learning situation and this was supported by (Ayres & Langone, 2008; Bellini et al., 2007; Burton et al., 2013).

Both IIVBI and CIVBI learning session has significantly related to the learning performance of moderate intellectual disability children, but it was observed that CIVBI experimental group was more active as compared to IIVBI and conventional group. This was due to the involvement of video-assisted instruction using the IVBI method that motivated the experimental group children to perform more actively as compared to the conventional group (Zhang et al., 2006).

The study found that IIVBI and CIVBI sessions were significantly more beneficial for children with moderate intellectual disability in developing new abilities compared to conventional methods. Moreover, the researchers have encountered the following limitations while conducting the present work: (1) Disabled children are unable to adjust to other children in a formal environment due to their parents' different socio-economic levels. Therefore, the concept of education for all should be made mandatory in both formal and informal contexts. (2) Due to the varying learning skills of the children based on their interests, considerable downsides may be detected during the implementation of technology-based training. As a result, different sorts of equipment should be utilised to teach new skills to children with or without disabilities. (3) Many challenges are detected against the policy of education and for this, the government, policymakers, parents, and teachers should take steps for delivering adjustments with acceptable outcomes. (4) Appropriate healthy educational environments are critical for enhancing cognitive development in children with or without disabilities. Therefore, introduction of new facilities for learning related resources can be useful in obtaining desired outcomes.

Conclusion

Each one of us has the right to education therefore providing education for all is compulsory without keeping any barriers irrespective of caste, religion, race, and ethnicity. In India, more research and policy implementation needs to focus on inclusive instruction for children with disabilities. The success and impact of interactive video-based instruction will largely depend on the impact of changing conventional views about technical innovation and financial criteria. Similarly, regular exercise in video learning allows the user to easily download, view, and reuse the learning resources or materials for quick remembering and longer retention (Seckman, 2017). It enables students to get information by browsing supported videos related to any search topic utilizing various web apps (Pulukuri & Abrams, 2020).

On the other hand, current improvements in multimedia have resulted in a variety of instructional video components such as video lectures, PowerPoint presentations, smart devices, LMS, virtual classrooms, online learning, and many others. In addition, regular usage of VBI greatly improves language skills difficulties in children with learning impairments (Xin & Rieth, 2001; Zhang et al., 2006). Moreover, VBI aids help in improving pupils' academic performance in the classroom (Ledbetter-Cho et al., 2017). It increases learners' capacity to remember material for a longer period and develop their interest in learning more about each topic. The IVBI technique can be effective for teaching children with and without disabilities various functionality skills, adaptive skills, daily living skills, and language skills.

The main focus of IVBI is to create an open learning environment for self-directed interaction, vocational training, increased activity level, more exposure towards an activity, reduction of stress regulation, and emotion recognition respectively. That means ultimately, the children can make themselves comfortable to learn more enthusiastically in a virtual setting as compared to the conventional teaching method. Accordingly, Standen & Brown (2005) findings conclude that virtual technology encourages the development of skills for independent life in a community for persons with intellectual disability for doing tasks like grocery shopping, meal preparation, traffic safety, and other functional abilities. In regard, IVBI intervention was very effective for taking the classes both in experimental and comparison groups. The experimental group's children found the classes interesting and insightful due to video lessons, while conventional group children showed less interest due to theoretical lectures and practice worksheets.

The present study is only limited to moderate intellectual disability children concerning their cognitive development using IVBI intervention for recording their performance. Therefore, the findings of the present work can apply to those research activities that have similar criteria of observation, relevance, and categorisation of the population. Also, results can be helpful for those who are working with assistive technology formats for delivering support to children with intellectual disability in their adaptive skills and functional skills using the IVBI method. However, IVBI intervention ensures benefits for teachers, learners, researchers, and society members in understanding the requirements and necessities for children with different types of disabilities. In contrast, Bassette et al. (2020) study explored the effectiveness of Visual-Biased Instruction (VBI) in skill learning for individuals with developmental disabilities in both school and community settings, revealing that the intervention effectively taught class management and passed on these skills to community members.

Consequently, the researchers have suggested employing IVBI for training cognitive skills as well as other functional abilities for teachers, parents, professionals, and researchers working with intellectual disabilities. Overall, research is needed to evaluate the effectiveness of IVBI treatment in social skills, language skills, daily living skills, and academic achievement. As a result, practicing knowledge acquisition, retention, and generalization of functionality skills can enhance performance and self-sufficiency in individuals with intellectual disabilities without external support.

Footnotes

Acknowledgment

The authors wish to thank all the selected rehabilitation authorities for granting permission in conducting smooth experimentation without any barriers. We would also like to thank all the participants for cooperating with us and making this experiment a successful work.

Declaration of conflicting interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Indian Council of Social Science Research (ICSSR) (RFD/2019-20/ST/EDU/40), New Delhi has provided financial support to the working author(s) for conducting the research work.

ORCID iD

Munmi Barman

References

AAIDD User's Guide Work Group . (2012). User’s guide to accompany the 11th edition of intellectual disability: Definition, classification, and systems of supports. Washington: American Association on Intellectual and Development Disabilities.

Afify

M. K.

(2020). Effect of interactive video length within e-learning environments on cognitive load, cognitive achievement and retention of learning. Turkish Online Journal of Distance Education, 21(4), 68–89. https://doi.org/10.17718/tojde.803360

Agnew

S. E.

Powell

M. B.

(2004).The Effect of Intellectual Disability on Children’s Recall of an Event Across Different Question Types. Law and Human Behavior, 28(3), 273–294.

Agran

Blanchard

Wehmeyer

Hughes

(2002). Increasing the Problem-Solving Skills of Students with Developmental Disabilities Participating in General Education. Remedial and Special Education, 23(5), 279–288. https://doi.org/10.1177/07419325020230050301

Ahn

Hwang

(2018). Cognitive Rehabilitation of Adaptive Behavior in Children with Neurodevelopmental Disorders: A Meta-Analysis. Occupational Therapy International, 1(7). https://doi.org/10.1155/2018/5029571

Akaike

(1987). Factor analysis and AIC. Psychometrika, 52(3), 317–332. https://doi.org/10.1007/bf02294359

Albrecht

Starnes

Benton

Bol

Gettings

Dagenhard-Trainer

(2021). Interactive digital art for individuals with intellectual disabilities. Journal of Intellectual Disabilities, 1–13. https://doi.org/10.1177/1744629520975554

American Psychiatric Association . (2015). Diagnostic and Statistical Manual of Mental Disorders (5th ed.). Washington, Dc: Author.

Anderson

Kazantzis

(2008). Social Problem-Solving Skills Training for Adults with Mild Intellectual Disability: A Multiple Case Study. Behaviour Change, 25(02), 97–108. https://doi.org/10.1375/bech.25.2.97

10.

Avcioglu

(2013). Effectiveness of video modelling in training students with intellectual disabilities to greet people when they meet. Educational Sciences: Theory and Practice, 13(1), 466–477.

11.

Ayres

K. M.

Langone

(2008). Video Supports for Teaching Students with Developmental Disabilities and Autism: Twenty-Five Years of Research and Development. Journal of Special Education Technology, 23(3), 1–8. https://doi.org/10.1177/016264340802300301

12.

Barman

Jena

(2021). Effect of interactive video-based instruction on learning performance in relation to social skills of children with intellectual disability. International Journal of Developmental Disabilities, 67(5), 1–14, https://doi.org/10.1080/20473869.2021.2004535

13.

Barua

Kaushik

J. S.

Gulati

(2017). Legal provisions, educational services, and health care across the lifespan for autism spectrum disorders in India. The Indian Journal of Pediatrics, 84(1), 76–82. https://doi.org/10.1007/s12098-016-2261-5

14.

Bassette

Titus‐Dieringer

Zoder‐Martell

Cremeans

(2020). The use of video‐based instruction to promote independent performance of physical activity skills in students with developmental disabilities in a school and community setting. Psychology in the Schools, 57(9), 1439–1456. https://doi.org/10.1002/pits.22414

15.

Bell

R. L.

Maeng

J. L.

Binns

I. C.

(2013). Learning in context: Technology integration in a teacher preparation program informed by situated learning theory. Journal of Research in Science Teaching, 50, 348–379. https://doi.org/10.1002/tea.21075

16.

Bellini

Akullian

Hopf

(2007). Increasing social engagement in young children with autism spectrum disorders using video self-modeling. School Psychology Review, 36(1), 80. https://doi.org/10.1080/02796015.2007.12087953

17.

Benkada

Moccozet

(2017). Enriched interactive videos for teaching and learning. In 2017 21st International Conference Information Visualisation (IV), 344–349. https://doi.org/10.1109/iV.2017.74

18.

Bereznak

Ayres

K. M.

Mechling

L. C.

Alexander

J. L.

(2012). Video self-prompting and mobile technology to increase daily living and vocational independence for students with autism spectrum disorders. Journal of Developmental and Physical Disabilities, 24(3), 269-285.

19.

Bigby

Frawley

Ramcharan

(2013). A Collaborative Group Method of Inclusive Research. Journal of Applied Research in Intellectual Disabilities, 27(1), 54–64. https://doi.org/10.1111/jar.12082

20.

Brown

D. A.

Lewis

C. N.

Lamb

M. E.

Stephens

(2012). The influences of delay and severity of intellectual disability on event memory in children. Journal of Consulting and Clinical Psychology, 80(5), 829–841. https://doi.org/10.1037/a0029388

21.

Burton

C. E.

Anderson

D. H.

Prater

M. A.

Dyches

T. T.

(2013). Video Self-Modeling on an iPad to Teach Functional Math Skills to Adolescents with Autism and Intellectual Disability. Focus on Autism and Other Developmental Disabilities, 28(2), 67–77. https://doi.org/10.1177/1088357613478829

22.

Burns

Pierson

Reddy

(2014). Working together: How teachers teach and students learn in collaborative learning environments. International Journal of Instruction, 7(1).

23.

Chan

(2019). Using digital storytelling to facilitate critical thinking disposition in youth civic engagement: A randomized control trial. Children and Youth Services Review, 107, 104522. https://doi.org/10.1016/j.childyouth.2019.104522

24.

Charlop-Christy

M. H.

Freeman

K. A.

(2000). A comparison of video modeling with in vivo modeling for teaching children with autism. Journal of autism and developmental disorders, 30(6), 537–552.

25.

Choi

H. J.

Johnson

S. D.

(2005). The effect of context-based video instruction on learning and motivation in online courses. The American Journal of Distance Education, 19(4), 215–227. https://doi.org/10.1207/s15389286ajde1904_3

26.

Cihak

Fahrenkrog

Ayres

K. M.

Smith

(2009). The Use of Video Modeling via a Video iPod and a System of Least Prompts to Improve Transitional Behaviors for Students with Autism Spectrum Disorders in the General Education Classroom. Journal of Positive Behavior Interventions, 12(2), 103–115. https://doi.org/10.1177/1098300709332346

27.

Contreras

M. I.

Santos

Bauza

C. G.

(2019). Video game-based tool for learning in the motor, cognitive and socio-emotional domains for children with Intellectual Disability, Entertainment Computing, https://doi.org/10.1016/j.entcom.2019.100301

28.

Dandashi

Karkar

A. G.

Saad

Barhoumi

Al-Jaam

El Saddik

(2015). Enhancing the Cognitive and Learning Skills of Children with Intellectual Disability through Physical Activity and Edutainment Games. International Journal of Distributed Sensor Networks, 11(6), 1. https://doi.org/10.1155/2015/165165

29.

Dekker

M. C.

Koot

H. M.

Ende

J. van der.

Verhulst

F. C.

(2002). Emotional and behavioral problems in children and adolescents with and without intellectual disability. Journal of Child Psychology and Psychiatry, 43(8), 1087–1098. https://doi.org/10.1111/1469-7610.00235

30.

Dessemontet

R. S.

Bless

Morin

(2011). Effects of inclusion on the academic achievement and adaptive behaviour of children with intellectual disabilities. Journal of Intellectual Disability Research, 56(6), 579–587. https://doi.org/10.1111/j.1365-2788.2011.01497.x

31.

Dučić

Gligorović

Kaljača

(2018). Relation between working memory and self‐regulation capacities and the level of social skills acquisition in people with moderate intellectual disability. Journal of Applied Research in Intellectual Disabilities, 31(2), 296–307. https://doi.org/10.1111/jar.12385

32.

Evmenova

A. S.

Graff

H. J.

Behrmann

M. M.

(2017). Providing access to academic content for high-school students with significant intellectual disability through interactive videos. Focus on Autism and Other Developmental Disabilities, 32(1), 18–30. https://doi.org/10.1177/1088357615609307

33.

Goharpey

Crewther

D. P.

Crewther

S. G.

(2013). Problem solving ability in children with intellectual disability as measured by the Raven’s Colored Progressive Matrices. Research in Developmental Disabilities, 34(12), 4366–4374. https://doi.org/10.1016/j.ridd.2013.09.013

34.

Goldsmith

T. R.

LeBlanc

L. A.

(2004). Use of technology in interventions for children with autism. Journal of Early and Intensive Behavior Intervention, 1(2), 166–178. https://doi.org/10.1037/h0100287

35.

Government of India (2020). National Education Policy 2020. https://www.education.gov.in/sites/upload_files/mhrd/files/NEP_Final_English_0.pdf

36.

Hong

E. R.

Ganz

J. B.

Mason

Morin

Davis

J. L.

Ninci

Neely

L.C.

Boles

M. B.

Gilliland

W. D.

(2016). The effects of video modelling in teaching functional living skills to persons with ASD: A meta-analysis of single- case studies. Elsevier: Research in developmental disabilities, 57, 158–169. https://doi.org/10.1016/j.ridd.2016.07.001

37.

Houwen

Visser

van der Putten

Vlaskamp

(2016). The interrelationships between motor, cognitive, and language development in children with and without intellectual and developmental disabilities. Research in Developmental Disabilities, 53-54, 19–31. https://doi.org/10.1016/j.ridd.2016.01.012

38.

L.T.

Bentler

P.M.

(1999). Cutoff Criteria for Fit Indexes in Covariance Structure Analysis: Conventional Criteria Versus New Alternatives. Structural Equation Modeling, 6(1), 1–55.

39.

Hughes

(1991). Independent performance among individuals with mental retardation: promoting generalization through self-instruction. Progress in Behavior Modification, 27, 7–35.

40.

Hung

I. C.

Chen

N. S.

(2018). Embodied interactive video lectures for improving learning comprehension and retention. Computers & Education, 117, 116–131. https://doi.org/10.1016/j.compedu.2017.10.005

41.

Iivari

Sharma

Ventä-Olkkonen

(2020). Digital transformation of everyday life–How COVID-19 pandemic transformed the basic education of the young generation and why information management research should care? International Journal of Information Management, 55, 102183. https://doi.org/10.1016/j.ijinfomgt.2020.102183

42.

Jenni

O. G.

Fintelmann

Caflisch

Latal

Rousson

Chaouch

(2014). Stability of cognitive performance in children with mild intellectual disability. Developmental Medicine & Child Neurology, 57(5), 463–469. https://doi.org/10.1111/dmcn.12620

43.

Joiner

. 2004. Supporting Collaboration in Virtual Learning Environments. Cyber Psychology & Behavior, 7(2), 197–200. https://doi.org/10.1089/109493104323024456

44.

Kellems

R. O.

Eichelberger

Cacciatore

Jensen

Frazier

Simons

Zaru

(2020). Using video-based instruction via augmented reality to teach mathematics to middle school students with learning disabilities. Journal of learning disabilities, 53(4), 277–291. https://doi.org/10.1177/0022219420906452

45.

Khanna

Kareem

(2021). Creating inclusive spaces in virtual classroom sessions during the COVID pandemic: An exploratory study of primary class teachers in India. International Journal of Educational Research Open, 2(2), 100038. https://doi.org/10.1016/j.ijedro.2021.100038

46.

Kirk

H. E.

Gray

Riby

D. M.

Cornish

K. M.

(2015). Cognitive training as a resolution for early executive function difficulties in children with intellectual disabilities. Research in Developmental Disabilities, 38, 145–160. https://doi.org/10.1016/j.ridd.2014.12.026

47.

Kline

R.B.

(2005). Principles and Practice of Structural Equation Modeling (2nd Edition ed.). New York: The Guilford Press.

48.

Kumar

D. D.

(2010). Approaches to Interactive Video Anchors in Problem-based Science Learning. J. Sci. Educ, 19(1), 13–19.

49.

Lazakidou

Retalis

(2010). Using computer-supported collaborative learning strategies for helping students acquire self-regulated problem-solving skills in mathematics. Computers & Education, 54(1), 3–13. https://doi.org/10.1016/j.compedu.2009.02.020

50.

Ledbetter-Cho

Lang

Moore

Davenport

Murphy

Lee

Watkins

(2017). Effects of video-enhanced activity schedules on academic skills and collateral behaviors in children with autism. International Journal of Developmental Disabilities, 63(4), 228–237. https://doi.org/10.1080/20473869.2017.1290022

51.

Liao

C. W.

Chen

C. H.

Shih

S. J.

(2019). The interactivity of video and collaboration for learning achievement, intrinsic motivation, cognitive load, and behavior patterns in a digital game-based learning environment. Computers & Education, 133, 43–55. https://doi.org/10.1016/j.compedu.2019.01.013

52.

Mechling

L. C.

Gast

D. L.

Langone

(2002). Computer-Based Video Instruction to Teach Persons with Moderate Intellectual Disabilities to Read Grocery Aisle Signs and Locate Items. The Journal of Special Education, 35(4), 225–240. https://doi.org/10.1177/002246690203500404

53.

Moemennasab

Rahemi

Ayatollahi

Aeen

(2002). The effect of video-based instruction on student’s cognitive learning. Journal of medical education, 1(3), 129–131. https://doi.org/10.22037/jme.v1i3.948

54.

O’Reilly

M. F.

Lancioni

Gardiner

Tiernan

Lacy

(2002). Using a Problem-Solving Approach to Teach Classroom Skills to a Student with Moderate Intellectual Disabilities within Regular Classroom Settings. International Journal of Disability, Development and Education, 49(1), 95–104.

55.

Pitchford

N. J.

Kamchedzera

Hubber

P. J.

Chigeda

A. L.

(2018). Interactive apps promote learning of basic mathematics in children with special educational needs and disabilities. Frontiers in Psychology, 9, 262. https://doi.org/10.3389/fpsyg.2018.00262

56.

Plavnick

J. B.

Sam

A. M.

Hume

Odom

S. L.

(2013). Effects of Video-Based Group Instruction for Adolescents with Autism Spectrum Disorder. Exceptional Children, 80(1), 67–83. https://doi.org/10.1177/001440291308000103

57.

Prater

M. A.

Carter

Hitchcock

Dowrick

(2011). Video self-modeling to improve academic performance: A literature review. Psychology in the Schools, 49(1), 71–81. https://doi.org/10.1002/pits.20617

58.

Pulukuri

Abrams

(2020). Incorporating an online interactive video platform to optimize active learning and improve student accountability through educational videos. Journal of Chemical Education, 97, 4505–4514. https://doi.org/10.1021/acs.jchemed.0c00855

59.

Riyanto

W. D.

Gunarhadi

(2017). The effectiveness of interactive multimedia in mathematic learning: Utilizing power points for students with learning disability. International Journal of Pedagogy and Teacher Education, 1(1), 55–62.

60.

Roldán-Álvarez

Martín

Haya

P. A.

(2021). Collaborative video-based learning using tablet computers to teach job skills to students with intellectual disabilities. Education Sciences, 11(8), 437. https://doi.org/10.3390/educsci11080437

61.

Sandlund

Mcdonough

Gerross

(2009). Interactive computer play in rehabilitation of children with sensorimotor disorders: A systematic review. Developmental Medicine & Child Neurology, 51(3), 173–179. https://doi.org/10.1111/j.1469-8749.2008.03184.x

62.

Schuchardt

Gebhardt

Mäehler

(2010). Working memory functions in children with different degrees of intellectual disability. Journal of Intellectual Disability Research, 54(4), 346–353. https://doi.org/10.1111/j.1365-2788.2010.01265.x

63.

Schwan

Riempp

(2004). The cognitive benefits of interactive videos: Learning to tie nautical knots. Learning and instruction, 14(3), 293–305. https://doi.org/10.1016/j.learninstruc.2004.06.005

64.

Seckman

(2017). Impact of Interactive Video Communication Versus Text-Based Feedback on Teaching, Social, and Cognitive Presence in Online Learning Communities. Nurse Educator, 43(1), 18–22. https://doi.org/10.1097/NNE.0000000000000448

65.

Sharma

(2018). Reflection on current status of inclusive education in India. International journal of research culture society, 2(3), 2456–6683.

66.

Sharma

Chunawala

(2015). Using diagrams in inclusive learning situations. Proceedings EpiSTEME, 6, 117–124.

67.

Sigman

McGovern

C. W.

(2005). Improvement in Cognitive and Language Skills from Preschool to Adolescence in Autism. Journal of Autism and Developmental Disorders, 35(1), 15–23. https://doi.org/10.1007/s10803-004-1027-5

68.

Singh

(2016). Inclusive education in India–concept need and challenges. Scholarly Research Journal for Humanity Science and English Language, 3(13), 3222–3232.

69.

Smogorzewska

Szumski

Grygiel

(2019). Theory of mind development in school environment: A case of children with mild intellectual disability learning in inclusive and special education classrooms. Journal of Applied Research in Intellectual Disabilities. https://doi.org/10.1111/jar.12616

70.

Söderström

Østby

Bakken

Ellingsen

K. E.

(2021). How using assistive technology for cognitive impairments improves the participation and self-determination of young adults with intellectual developmental disabilities. Journal of intellectual disabilities, 25(2), 168–182. https://doi.org/10.1177/1744629519882582

71.

Standen

P. J.

Brown

D. J.

(2005). Virtual reality in the rehabilitation of people with intellectual disabilities. Cyberpsychology & Behavior, 8(3), 272–282. https://doi.org/10.1089/cpb.2005.8.272

72.

Suharja

E. S.

Februanti

Kartilah

(2019). Interactive Video Improve the Brushing Skills of Mild Mentally Disabled Students. In Journal of Physics: Conference Series, 1179(1), 012062. https://doi.org/10.1088/1742-6596/1179/1/012062

73.

Sustain–able Development Goals . (2015). Transforming our World: The 2030 Agenda for Sustainable Development. https://social.desa.un.org/2030agenda-sdgs

74.

Tuma

(2021). The use of educational technology for interactive teaching in lectures. Annals of Medicine and Surgery, 62, 231–235. https://doi.org/10.1016/j.amsu.2021.01.051

75.

UNICEF . (2016). Making Schools Accessible to Children with Disabilities. New Delhi United Nations Children’s Fund.

76.

United Nation Convention . (2015). The Global Action on Disability (GLAD) Network. https://gladnetwork.net/

77.

Van Nieuwenhuijzen

Vriens

(2012). Cognitive skills and social information processing in children with mild to borderline intellectual disabilities. Research in Developmental Disabilities, 33(2), 426–434. https://doi.org/10.1016/j.ridd.2011.09.025

78.

West

S. G.

Taylor

A. B.

(2012). Model fit and model selection in structural equation modeling. In Handbook of structural equation modeling (pp. 209–231). New York, NY: The Guilford Press).

79.

Wilkes-Gillan

Joosten

(2016). Technology-based interventions were found to have evidence of effectiveness on a range of outcomes, including social problem solving and facial and emotional processing skills for individuals with autism spectrum disorders. Australian Occupational Therapy Journal, 63(2), 135–136. https://doi.org/10.1111/1440-1630.12274

80.

Wishart

J. G.

Willis

D. S.

Cebula

K. R.

Pitcairn

T. K.

(2007). Collaborative Learning: Comparison of Outcomes for Typically Developing Children and Children With Intellectual Disabilities. American Journal on Mental Retardation, 112(5), 361. https://doi.org/10.1352/0895-8017(2007)112[0361:CLCOOF]2.0.CO;2

81.

Guo

Wang

Zeng

(2021). Integrating spherical video-based virtual reality into elementary school students’ scientific inquiry instruction: effects on their problem-solving performance. Interactive Learning Environments, 29(3), 496–509. https://doi.org/10.1080/10494820.2019.1587469

82.

Xin

J. F.

Rieth

(2001). Video-assisted vocabulary instruction for elementary school students with learning disabilities. Information technology in childhood education annual, 2001(1), 87–103.

83.

Yakubova

Hughes

E. M.

Baer

B. L.

(2019). Supporting students with ASD in mathematics learning using video-based concrete-representational-abstract sequencing instruction. Preventing School Failure: Alternative Education for Children and Youth, 1–7. https://doi.org/10.1080/1045988x.2019.1627999

84.

Zhang

Zhou

Briggs

R. O.

Nunamaker

J. F.

(2006). Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness. Information & Management, 43(1), 15–27. https://doi.org/10.1016/j.im.2005.01.004