Citation

Shaheed, I. M., Khudhair, K. T., & Hasan, N. F. (2026). Content Validity Testing of Items for Determining the Appropriateness of a Computer Science-Specific Learning Taxonomy Instrument. International Journal of Research, 13(4), 155–167. https://doi.org/10.26643/ijr/edupub/12

Iman Mousa Shaheed^1, *, Kifah Taha Khudhair², Noor Flayyih Hasan³

¹General Directorate of Education in Najaf, Kufa department of education, Najaf, Iraq

²Technical College of Management – Kufa, Al-Furat Al-Awsat Technical University, Kufa, 54003, Iraq

³Southern Technical University, Thi-Qar Technical College, Department of Accounting Techniques, Iraq

*Corresponding author: eman_musa21@yahoo.com

Abstract

Classification of learning objectives using taxonomies can substantially impact teaching and learning processes if the classifications are appropriate to the subject being taught. There is currently a trend toward the development of computer science-specific taxonomies. However, a tool for determining a new taxonomy’s appropriateness does not exist yet due to a lack of agreement regarding the appropriateness of a taxonomy. The purpose of this study was to determine the content validity of an instrument for assessing the appropriateness of a computer science-specific taxonomy. Five individuals specializing in computer science instruction judged the content validity of individual items on a four-point scale. These experts recommended minor revisions to improve the clarity or wording of the items, and these suggestions were incorporated into the instrument. The individual content validity index (I-CVI) and scale content validity index (S-CVI) were calculated. All the I-CVIs were 1.0, and the average scale content validity index was 1.0. The panel determined that all the items possessed sufficiently high content validity. This degree of content appropriateness indicates that the next stage of instrument development can occur.

Keywords: Learning Taxonomy; Appropriateness; Instrument Development; Content Validity Index.

1.0   Introduction

Learning taxonomies are useful planning tools for instructors, helping them to assess curriculum and related educational objectives. With respect to computer science, educators have widely used Bloom’s taxonomy and its revised versions [1, 2]. However, numerous other computer science-specific taxonomies have also been recommended [3-5] because of the original taxonomy’s unsuitability for learning computer science subjects [6]. Teodorescu, Bennhold [7] asserted that to help educators plan and assess their teaching, taxonomies must suit their goals and include subject-specific requirements.

According to Kropp, Stoker [8], a major problem is providing evidence of a taxonomy’s appropriateness including the development of a valid statistical methodology and models.

Unfortunately, there are few studies of the development of such models. Hauenstein [9] suggested five general rules of taxonomy evaluation: it should be applicable, inclusive, consist of categories that are independent from one another, reflect a consistent order, and use terms that are relevant to the subject area. Inclusivity prevents standards from being omitted, and mutual exclusivity prevents overlapping categories in a taxonomy.

The purpose of this study was to determine the content validity of an instrument to assess the appropriateness of a computer science-specific taxonomy. The results address the existing knowledge gap, and this instrument will provide computer science educators with a reliable, valid, and convenient tool for selecting the best taxonomy to use in their teaching practices.

2.0 TAXONOMY Appropriateness

When describing the appropriateness of a taxonomy, one must first determine the subject-specific specifications of the taxonomy. To our knowledge, no studies have discussed these specifications in relation to computer science.

To address this gap in the literature, the authors reviewed 40 studies of the application of Bloom’s taxonomy in computer programming courses. The aim was to answer the following key research questions: What are the deficiencies affecting currently used learning taxonomies with regard to computer-programming courses?

To answer this question, qualitative content analysis techniques were used to analyze statements about the computer programming-related shortcomings of Bloom’s taxonomy. These shortcomings were used to develop specifications for the appropriate computer science-specific learning taxonomy. Since the current adoption of Bloom’s taxonomy by ACM and IEEE Computer Society [10] to categorize the learning results of the basic programming course in the prospectus of the ACM/IEEE-CS, this search was limited to investigating the weaknesses of the original Bloom’s taxonomy and its revised versions. However, this analysis may also indicate other weaknesses in existing Bloom-based taxonomies.

The next sub-section describes the study performed to identify the specifications of a computer science-specific taxonomy and the dimensions required to evaluate the appropriateness of this learning taxonomy.

2.1   Specifications Identification

The literature review in this investigation involved the use of search terms that were derived from the research question, for example, “taxonomies of learning”, “Computer science education”, “computer programming”, and “Bloom’s taxonomy”. This data mining involved the use of four major electronic databases: the ACM Digital Library, ScienceDirect, Springer, and Google Scholar. The title, abstract, and keywords were reviewed in the search for published journal papers, conference proceedings, workshops and excerpts from the relevant literature.

A qualitative content analysis was conducted using the NVivo version 10 qualitative software database (QSR International Pty Ltd, Burlington, MA, USA) and was guided by the procedure of Edwards-Jones [11] to partially automate our analysis of the discussion sections in the reviewed articles.

In particular, one of the authors performed a constant comparison analysis [12] of both deductive and inductive coding approaches [13]. In the deductive phase, the aforementioned rules by Hauenstein [9] were considered. This step was performed by reading the entire set of data. Then, the author chunked the data into smaller meaningful parts. The author then labeled each chunk with a descriptive title or a “code”. NVivo was used to highlight segments of the text that included coding representing a specific weakness. Each new chunk of data was then compared with previous codes so that similar chunks were labeled with the same code. After all the data were coded, the codes were grouped by similarity, and a theme was identified and documented based on each grouping.

As a result, comprehensive computer science-specific taxonomy specifications are proposed, namely, consistency, inclusivity, hierarchical adequacy, representativeness, usability, coherence, mutual exclusivity, and dimensional adequacy. Table 1 presents these primary dimensions along with the approach used and their descriptions.

To ensure inter-rater reliability, the data were coded first. Themes and randomly selected sample statements related to these themes were then given to two reviewers who had taken a course in qualitative research methods. The reviewers were Ph.D. holders in education whose research interests included computer science education. The reviewers were asked to code the documents based on the themes. The agreement between the two experts’ reports measured 86%.

Table 1 Computer Science-Specific Taxonomy Specifications

No	Dimension	Approach	Description
1	Usability	Inductive	The taxonomy should categorize programming learning objectives in a simple way that could break these objectives into their components (i.e. task(s) and knowledge(s)).
2	Consistency	Deductive	The taxonomy should involve a dependable classification and interpretation of programming learning outcomes. These outcomes should always be expressed the same way.
3	Learnability	Inductive	Taxonomic categories and their interpretations should be comprehensible.
4	Hierarchical adequacy	Deductive	The hierarchy of categories should effectively describe programming learning objectives.
5	Dimensional adequacy	Inductive	The taxonomy should have two distinct dimensions (knowledge types and cognitive processes) to successfully describe the constructive learning objectives of programming. According to Airasian and Miranda [14], a two-dimensional approach allows educators to create stronger objectives that address increasingly complex instruction methods.
6	Mutual exclusivity	Inductive	Each learning objective should be assigned to only one category.
7	Inclusivity	Deductive	The taxonomy should include a sufficient list of all necessary programming knowledge types and skills for the user to classify all programming learning standards.
8	Representativeness	Deductive	The taxonomy should use common relevant terms to describe programming skills, knowledge types, and competencies required for each skill. The programming knowledge framework should be considered [15, 16].

3.0   Instrument development

The development process of Lynn [17] was used to guide the content development for this instrument. In this process, when content is being developed for an affective measure such as one of taxonomic appropriateness, two sub-processes occur: development and judgment. Development involves the identification of dimensions or sub-dimensions and extends to item generation and the subsequent integration of items into a suitable form, according to Lynn [17]. Judgment involves determining whether the given content and instrument are sufficiently valid [17]. According to Turner, Quittner [18], during initial instrument development, a conceptual framework should be identified. This framework should be representative so that the domain content is specific and relates to the subject area. This specificity is achieved by reviewing the related literature, during which potential items are identified. Once the preliminary scope of the taxonomy has been identified, the proposed content is analyzed to achieve a satisfactory final structure. 

3.1   Conceptual Framework and Domain Content Identification

Insufficient information exists on theories of measuring taxonomy appropriateness, and no substantive literature regarding the application of theoretical validity frameworks are yet available. However, we recommended that the framework presented in Table 1 be considered when developing a learning taxonomy for computer programming purposes. In addition, the taxonomy framework presented in Table 1 should include items that are representative of the domain of computer programming and that adequately support the validity of the construction. This representativeness is achieved by using the framework to guide the selection of specific content deemed suitable for fully developing the instrument.

3.2   Identification of Items

The identification of items involved writing items for the scales. Initially, items from a previously validated questionnaire, specifically, the Measurement Scales for Perceived Usefulness and Perceived Ease of Use, by Davis [19], was examined and adapted. Then, suitable items were written for each scale based on a review of the literature [3, 20-37], and these items were incorporated into the taxonomy framework and were finally related to particular dimensions. Table 2 shows the items developed for each dimension.

Table 2 Taxonomy Appropriateness Items.
Dimension	Items
1. Usability	1.1 This taxonomy is easy to use.
	1.2 This taxonomy is flexible in describing learning objectives.
	1.3 Using this taxonomy is effortless.
	1.4 This taxonomy gives me more control over the activities in my course.
2. Consistency	2.1 This taxonomy can be used to interpret programming learning tasks every time.
	2.2 This taxonomy can be used to interpret programming learning knowledge every time.
	2.3 This taxonomy can be used to classify programming learning outcomes every time.
3. Learnability	3.1 The categories in this taxonomy are comprehensible.
	3.2 The categories in this taxonomy can be clearly interpreted.
	3.3 This taxonomy is readable.
4. Hierarchical adequacy	4.1 The ordering of the taxonomy’s skill sets appropriately reflects the programming learning process.
	4.2 The ordering of the taxonomy’s knowledge types appropriately reflects the programming learning process.
	4.3 The ordering of the taxonomy’s categories appropriately reflects programming learning objectives.
5. Dimensional adequacy	5.1 This taxonomy includes enough distinctive dimensions of knowledge that can be used to successfully describe constructive programming learning objectives.
	5.2 This taxonomy includes enough distinctive dimensions of cognitive that can be used to successfully describe constructive programming learning objectives.
	5.3 This taxonomy includes enough distinctive categories that can be used to successfully describe constructive programming learning objectives.
6. Mutual exclusivity	6.1 When using this taxonomy, each knowledge type required in programming learning can be assigned to a single category.
	6.2 When using this taxonomy, each programming learning skill can be assigned to a single category.
	6.3 When using this taxonomy, each programming learning objective can be assigned to a single category.
7. Inclusivity	7.1 The set of knowledge types in this taxonomy include all necessary knowledge types that students must know to perform a given programming learning task.
	7.2 The skills in this taxonomy include all the necessary skills that students must acquire to perform a given programming learning task.
	7.3 The knowledge types in this taxonomy include all appropriate types that students must know to perform a given programming learning task.
	7.4 The skills in this taxonomy include all appropriate skills that students must acquire to perform a given programming learning task.
8. Representativeness	8.1 The categories in this taxonomy are relevant to learning computer programming.
	8.2 The knowledge types in this taxonomy are relevant to knowledge required to perform computer programming learning tasks.
	8.3 The skill sets in this taxonomy are relevant to skills that must be acquired by students to perform computer programming learning tasks.

4.0   Measuring Content Validity

Once the items have been generated, the validity of an item and of the overall instrument must be quantitatively determined [17]. In doing this, researchers frequently calculate a content validity index (CVI). Hambleton, Swaminathan [38] first presented this index and advocated its use in nursing research conducted by Waltz and Bausell [39].

Many factors guided the selection of this index, including its ease of calculation and understanding. In contrast, the content validity ratio (CVR) developed by Lawshe [40], for example, is easy to calculate but not as easy to interpret [41]. Another desirable quality of a content validity measure is that it yields item-level information that can be used to refine or discard items and a summary of the content validity of the overall scale [41].

The CVI is the percentage of respondents who assign an item a score of 3 or 4 on a 1–4 scale of relevance or representativeness. It has been recommended that an individual CVI (I-CVI) and a scale CVI (S-CVI) should be calculated separately and that the S-CVI be reported [39, 41-43].

Polit and Beck [42] preferred the S-CVI in cases where more content-expert panel members are involved because one hundred percent agreement is not feasible. The S-CVI is determined by averaging I-CVI scores. When six or more experts are involved, Lynn [17] recommended a minimum I-CVI of 0.78. However, Waltz and Bausell [39] recommended a minimum S-CVI value of 0.90 for a valid scale in which items should be retained. In this study, we use both the I-CVI and S-CVI to determine the content validity of statements related to taxonomy appropriateness.

4.1   Expert Panel

Lynn [17] argued that at least three experts should be consulted when performing content validation. Our expert panel included five subject matter experts with more than 10 years of teaching programming experience. These experts were invited to evaluate the content validity based on the I-CVI and S-CVI. Each respondent received an informational email that included a hyperlink to a questionnaire. Survey security was maintained using Secure Sockets Layer technologies to protect confidentiality, and no personal identifiers were collected. A four-point scale was used to evaluate the content validity, and the values were matched with verbal descriptions of taxonomic appropriateness as follows: 1 = the item is not representative; 2 = the item requires major revisions to be representative; 3 = the item requires minor revisions to be representative; 4 = the item is representative. The CVI was calculated as the percentage of experts who selected 3 or 4 when scoring the items. As prescribed in the proposed methodology of our study, both the I-CVI and S-CVI were calculated. The average scale CVI (S-CVI/Ave) was determined from all the I-CVI values. The target SCVI/Ave value, according to Polit and Beck [42], is 0.9.

For greater reliability, we then calculated a modified kappa statistic (k*) described by Polit, Beck [41]. According to Wynd, Schmidt [44], the kappa statistic is an important supplement to the CVI because it indicates the degree of agreement beyond chance. To assess the degree of agreement based on the value of κ*, the guidelines by Landis and Koch [45] are used.

5.0   Results and Discussion

Five experts (1 female) agreed to participate in the study. The expert panel consisted of two domain experts, each with more than six years of programming teaching experience. Additionally, three members of the panel had more than 11 years of experience, and two had more than 15 years of experience. The experts currently teach programming and are familiar with the classification of learning objectives in accordance with Bloom’s taxonomy. The panel was given an opportunity to provide feedback on whether they identified mistakes or ambiguities in any part of the instrument. They were also encouraged to suggest ways to improve the instrument.

According to Polit and Beck [42], the I-CVI of a new instrument should range between 0.78 and 0.80. As indicated, all the I-CVI scores for this instrument were 1.0. Therefore, all the items were retained in the questionnaire. Following the recommendations of Lynn [17], testing of a psychometric instrument should be conducted next. The expert panel assigned the instrument I-CVI scores of 1.0 (Table 3). Thus, the S-CVI/Ave value was recorded as 1.0, confirming that each individual item can be retained. The 26 items received an I-CVI value of 1.0. Because the CVI scores were consistently high, we concluded that none of the experts’ suggestions regarding item content needed to be adopted. The high degree of concurrence regarding taxonomy appropriateness among the respondents indicates that the instrument for assessing taxonomy appropriateness is adequate for progression to the next step of instrument development.

A modified kappa statistic (k*) was calculated to determine if there was agreement between the raters’ judgments regarding whether the 26 items regarding taxonomy appropriateness were relevant. There was high agreement between the five raters’ judgments of all the items: κ* = 1.0.

Table 3 Content validity indices (I-CVI and S-CVI)

Items	I-CVI	S-CVI/ave	k*	No. of Respondents
1. Usability
1.1 This taxonomy is easy to use.	1.0		1.0	5
1.2 This taxonomy is flexible in describing learning objectives.	1.0		1.0	5
1.3 Using this taxonomy is effortless.	1.0		1.0	5
1.4 This taxonomy gives me more control over the activities in my course.	1.0		1.0	5
2. Consistency
2.1 This taxonomy can be used to interpret programming learning tasks every time.	1.0		1.0	5
2.2 This taxonomy can be used to interpret programming learning knowledge every time.	1.0		1.0	5
2.3 This taxonomy can be used to classify programming learning outcomes every time.	1.0		1.0	5
3. Learnability
3.1 The categories in this taxonomy are comprehensible.	1.0		1.0	5
3.2 The categories in this taxonomy can be clearly interpreted.	1.0		1.0	5
3.3 This taxonomy is readable.	1.0		1.0	5
4. Hierarchical adequacy
4.1 The ordering of the taxonomy’s skill sets appropriately reflects the programming learning process.	1.0		1.0	5
4.2 The ordering of the taxonomy’s knowledge types appropriately reflects the programming learning process.	1.0		1.0	5
4.3 The ordering of the taxonomy’s categories appropriately reflects programming learning objectives.	1.0		1.0	5
5. Dimensional adequacy
5.1 This taxonomy includes enough distinctive dimensions of knowledge that can be used to successfully describe constructive programming learning objectives.	1.0		1.0	5
5.2 This taxonomy includes enough distinctive dimensions of cognitive that can be used to successfully describe constructive programming learning objectives.	1.0		1.0	5
5.3 This taxonomy includes enough distinctive categories that can be used to successfully describe constructive programming learning objectives.	1.0		1.0	5
6. Mutual exclusivity
6.1 When using this taxonomy, each knowledge type required in programming learning can be assigned to a single category.	1.0		1.0	5
6.2 When using this taxonomy, each programming learning skill can be assigned to a single category.	1.0		1.0	5
6.3 When using this taxonomy, each programming learning objective can be assigned to a single category.	1.0		1.0	5
7. Inclusivity
7.1 The set of knowledge types in this taxonomy include all necessary knowledge types that students must know to perform a given programming learning task.	1.0		1.0	5
7.2 The skills in this taxonomy include all the necessary skills that students must acquire to perform a given programming learning task.	1.0		1.0	5
7.3 The knowledge types in this taxonomy include all appropriate types that students must know to perform a given programming learning task.	1.0		1.0	5
7.4 The skills in this taxonomy include all appropriate skills that students must acquire to perform a given programming learning task.	1.0		1.0	5
8. Representativeness
8.1 The categories in this taxonomy are relevant to learning computer programming.	1.0		1.0	5
8.2 The knowledge types in this taxonomy are relevant to knowledge required to perform computer programming learning tasks.	1.0		1.0	5
8.3 The skill sets in this taxonomy are relevant to skills that must be acquired by students to perform computer programming learning tasks.	1.0		1.0	5
Scale		1.0
I-CVI, individual content validity Index; S-CVI/ave, average scale content validity index; k*, modified kappa statistic

6.0   Conclusions

The responses of the expert panel of programming instructors indicate that the proposed content presents a high degree of taxonomic appropriateness. We also found consistency in terms of agreement among the respondents, indicating that progression to the next phase of instrument development can commence. The 26 items that were considered in the taxonomy appropriateness questionnaire will be psychometrically tested through a pilot evaluation using item response theory. This step will determine whether construct validity in the context of computer programming as demonstrated by the questionnaire serves as an indication of taxonomy appropriateness. The outcomes of this next stage may influence the future selection of taxonomies that are appropriate for this subject area.

Acknowledgement

The authors are thankful to anonymous reviewers whose comments significantly improved this manuscript.

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Citation

Nwonovo, O. S. (2026). VAR’S Applicability to Rehabilitate Violent Victims in Sudan. Think India Quarterly, 29(1), 77–85. https://doi.org/10.26643/think/1

^**Oluchukwu Sunday Nwonovo***

Department of Sociology and Anthropology,

Faculty of Social Sciences and Humanities,

Enugu State University of Science and Technology, Agbani

Email: oluchukwu.nwonovo@esut.edu.ng

Corresponding author***

 ORCID: https://orcid.org/0009-0007-7697-2323

Abstract

The victims’ humanitarian problems have been made worse by the international community’s passivity and disregard for the humanitarian crisis brought on by political upheaval in Sudan. Humanitarian aid is still inadequate, even when it is given. Thus, this article investigates the viability of rehabilitating and empowering victims of political upheaval in Sudan through the use of virtual and augmented reality. Newspapers, journal articles, textbooks, technology blogs, social media commentary, and websites were the secondary sources of data for the study. In order to eliminate obvious duplications and difficulties in handling the issue, consequently endangering the victims’ humanitarian requirements, the paper concludes by recommending the immediate use of virtual reality and augmented reality in rehabilitating and re-empowering victims of the Sudanese crisis. Adopting this technology in a timely manner can greatly lessen the victims’ humanitarian requirements and the aftermath of the war, given the precarious nature of the situation. The most effective approach to accomplish this is for the UN High Commissioner for Refugees and other relevant parties to use technical visuals and animation from augmented reality and virtual reality into the treatment of the victims.

Keywords:  Crisis, Humanitarian needs, VAR, Victims, Violence

Introduction

            Due to widespread displacement, conflict, the impending collapse of the healthcare system, and economic suffering, the Sudanese crisis is currently expanding at the highest rate in the world (Chinweze et al., 2024). Ninety percent of Sudanese people suffer from emergency levels of hunger, and 1.8 million suffer from severe food insecurity. Humanitarian problems have also been exacerbated by ongoing power struggles between and among various interest groups, which have resulted in violent conflicts and unrest (World Food Program WFP, 2024). A power battle between General Mohamed Hamdan Dagalo’s paramilitary organization, the Rapid Support Force (RSF), and General Abdul Fattah al-Burhan’s military is the cause of the current political upheaval. Unimaginable deaths and the largest humanitarian disaster in history have resulted from the turmoil (Chinweze et al., 2024).Before the current conflict, 15.8 million Sudanese needed humanitarian aid due to long-term political turbulence and economic challenges. Nearly 25 million people, or more than half of the country’s population, are facing a humanitarian crisis as a result of the continuous violence. Reports of mass murders, displacements, and restrictions on humanitarian access exacerbate humanitarian problems, endangering the entire Central African area (International Rescue Committee, 2024). According to WFP (2020), despite international cooperation during Sudan’s biggest hunger crisis less than 20 years ago, the Sudanese people appear to have been overlooked in a disturbance that is currently endangering the stability and peace of the whole African area. Unfortunately, thousands of people have died and nearly eight million have been displaced as a result of the unrest.According to the International Rescue Mission (2024), the dangerous civilian displacements are putting further pressure on Sudan’s healthcare system. Cholera and measles outbreaks have killed over 1,000 Sudanese children, and as of December 2023, there were over 8,500 probable cases. The United Nations International Children’s Emergency Fund reports that the fighting killed 330 children and injured over 1,900 Sudanese (UNICEF, 2023). Over 13 million children are in dire need of humanitarian aid, including protection, food, water, and medical care, as a result of severe limitations on access to vital life-saving services.Sudan’s future seems to be in danger, according to UNICEF’s observations. The residents are imprisoned in a never-ending nightmare, mistreated, injured, uprooted, caught in a crossfire, and exposed to illness and starvation. According to UNICEF (2023), the lack of sufficient water puts many Sudanese people at risk for starvation, dehydration, and diarrhoea. There are now 14,836 extremely malnourished children under five, and this number is predicted to rise due to public health threats. Additionally, children are now far more vulnerable to illness due to the looting and destruction of hospitals, vaccines, and other medical facilities. Lack of energy and insufficient medical supplies, such oxygen and functional incubators, make this considerably more difficult.Islamic Relief (2023) claims that political upheaval has interfered with Sudan’s already inadequate social services and educational system. The nation’s healthcare sector is in horrible state, with the majority of medical experts leaving the country and medical facilities being plundered and destroyed, while about 58% of schools have been forced to close. According to Basher, Sharif, and Cafiero (2023), millions of Sudanese urban residents have lost their jobs, raising the nation’s humanitarian requirements. UN Secretary-General António Guterres’ statement that the horrific reports emanating from Sudan are disheartening makes logic. Over 4000 people have been hurt, hundreds have fled their homes, and at least 450 people—including four members of the UN family—have died. Many hospitals are being taken over by armed groups, healthcare facilities are crumbling, and people are terrified and confined to their houses with little to no access to food, medicine, water, or petrol. Residents of Blue Nile and North Kordofan are reportedly fleeing their homes due to strong rumours of violent clashes throughout Sudan. This political turmoil has started a fire that has the potential to aggravate the already dire humanitarian situation and postpone the African region’s development for decades.The fact that funds intended for the nation’s socioeconomic growth are instead being used to handle urgent humanitarian needs including emergency assistance, housing for displaced people, and medical facilities is annoying. Long-term economic growth is hampered and already scarce resources are burdened. Due to significant interruptions to enterprises that account for 21% of the country’s GDP, Sudan will probably experience a protracted economic downturn following the conflict (Basher, Sharif & Cafiero, 2023). The agricultural industry, which accounts for 32.7% of the GDP and is vital to many Sudanese, would suffer the most from a shortage of petrol and fertiliser. Millions of Sudanese will thus be in grave danger of starving, which will raise the price of products and cause inflation.To date, however, no meaningful strategy has been used to realign crisis management with standard operating procedures for realistic results and the decrease of humanitarian crises. After the crisis, many of its victims experience worsening mental health. The way the humanitarian situation is handled should be a turning point for the victims, but instead it has turned into a dull experience. In Africa, this methodical approach to managing humanitarian crises has become the norm. The use of virtual reality and augmented reality by Florida Drug Courts in the US to rehabilitate drug addicts and inmates is an urgently needed method for this (Christopher, 2018). This is so crucial that it needs to be included in the treatment of victims of political unrest in Sudan. According to Ajah, Nnam, Ajah, Idemili-Aronu, Chukwuemeka, and Agboti (2021), using augmented reality and virtual reality therapy programs improves participants’ rehabilitation, reintegration, and re-empowerment into society. This and similar actions are a long way from controlling Sudan’s political unrest. The victims’ situation is made worse by systemic flaws connected to the present humanitarian issues. Identity crises, poorly trained workforce, armament infiltration, systematic delays in the delivery of humanitarian goods, and inefficient humanitarian administration are some of these flaws. The main result of these issues is that the victims of Sudan’s continuous political upheaval suffer from psychological diseases and the accompanying pain and suffering.However, other studies have looked at the difficulties and issues mentioned above (see Ferragamo & Roy, 2024; Marsden, 2023; McCarthy, 2023; Mutasa & Virk, 2017; Ottaway & El-Sadany, 2012). Our understanding of the problems caused by political upheaval and potential solutions is greatly advanced by these research. The studies are particularly valued for emphasising the urgent need for humanitarian attention, identifying hostilities between the various groups involved in the conflicts, allocating more funds for humanitarian purposes, supplying more humanitarian supplies, motivating more stakeholders to help put an end to the unrest, and much more. The humanitarian crisis management strategy that could establish the connections between the psychologies and social thought patterns of the victims of the political unrest, which virtual reality (VR) and augmented reality (AR) strongly promise to accomplish with far-reaching benefits and ease, has not been fully explained by the numerous studies on the Sudanese crisis. The overlapping therapies could help the victims overcome mental suffering and change their perspectives by using visualised psychosocial conflict-scene reconstructions and technological imaging. Thus, the current study examines what is effective in resocialising the victims in order to produce mental-sea shift in them: attitudinal transformation and inner-behavioral alteration employing technology-driven conflict scene attention recapture. It is very important to incorporate this method into the management of the humanitarian crisis in Sudan for better outcomes and the victims’ re-empowerment.

VAR’s Conceptual Overview

Using computer software to create virtual worlds with real-world characters and phenomena is known as virtual reality, or VR. “These imaginary environments are called virtual worlds, where viewers connect by wearing headsets and can interact with things in the virtual world using computer keyboards, mouse, or wired gloves,” in the words of Ajah et al. (2021: The experience of presence is significantly enhanced by the virtual world. With no components taken from actual film or recordings, virtual reality is a complete recreation of real-life occurrences. Tom Caudell, a researcher at Boeing, invented augmented reality (AR) in 1990 by adding computer-generated visuals to elements to create what looks like a real-world setting (Alice, 2017; Christopher, 2018; Ajah, Ajah & Obasi, 2019).

“AR technology” refers to devices or wearable screens that superimpose text, music, pictures, or videos on top of our experience of the real environment. The location and context of the physical world are incorporated into this digital data. AR is different from VR in that it blends the real world with computer-generated objects. In other words, augmented reality (AR) is the use of computer software to generate people, sounds, sceneries, or events that enhance real-world happenings. Imagine rebuilding an entire wedding party from intermittent wedding video clips, or reconstructing a whole crime scenario from early security camera records before the camera was broken. Augmented reality (AR) improves real-world events with simulated sounds or effects, in contrast to virtual reality (VR), which uses computer software to duplicate whole events without any portion of the virtual environment originating from real-world recordings. AR makes use of software technology to add features of support to the reality we live in today. AR allows for perfect interaction between the real and virtual worlds (Ajah et al, 2021:3-4).

Using VAR to Rehabilitate Victims of Sudanese Violence

            By simulating scenarios, virtual reality (VR) and augmented reality (AR) can enable victims of political unrest in Sudan envision various solutions to their challenging circumstances without causing them any discomfort. Because both technologies exhibit a high degree of viewer presence, the victims receive coaching and rehabilitation on better alternative ways to perceive the environment, whether it be virtual or real. The UN High Commissioner for Refugees and other conflict stakeholders might consider from views that would empower the victims and help them rediscover who they are thanks to data from these exercises, which broaden the victims’ perspectives more than therapy sessions.VR and AR are essential for healing and re-empowering victims of Sudan’s continuous political instability, as the previously described image clearly demonstrates. The victims will gain from the application in three ways: (1) by receiving training and upskilling to assist them find work and reintegrate economically into society. (2) Changing the way the patients think in order to stop mentally upsetting tendencies and encourage healing. (3) Teach victims who are currently struggling about everyday life and traditional social values. VR and AR can certainly be replaced by therapists and psychologists, but since they are not mutually exclusive, the UN High Commissioner for Refugees and other conflict parties may use both to enhance results. Few theoretical and empirical studies have examined the application of VR and AR in the rehabilitation of victims of political unrest and violence. This paper’s significance arises from the urgent need to close this gap in literature and knowledge.

International Community and their Response to Violence in Sudan Up to This Point

            Numerous swift and forceful measures have been made by nations all over the world, including those in Sub-Saharan Africa, to handle the political unrest; in certain cases, these efforts have been effective. According to the Inter-governmental Authority on Development (IGAD, 2024), the Quad for Sudan, which is made up of the United States, the United Kingdom, Saudi Arabia, and the United Arab Emirates, issued a press release on April 28, 2024, urging peace and an immediate end to hostilities between the parties involved in the political unrest.In a similar news release, UN Secretary-General António Guterres urged the warring parties to halt hostilities in observance of Ramadan (United Nations, 2024). The United Nations Security Council (2024) demanded that hostilities end immediately and that peace talks begin again. Furthermore, the African Union Peace and Security Council asked that all parties involved in the issue put an end to hostilities during their emergency session, according to the Sudan Tribune (2023). Former South African President Thabo Mbeki has called for an urgent end to the conflict, according to Sudan War Monitor (2023). Former Sudanese Prime Minister Abdalla Hamdok warned that political upheaval in Sudan could lead to regional conflict in Africa, according to The Guardian (2023).The United Nations Women’s Organization has been collaborating with Sudanese women and civic organisations to quickly assess the needs of young girls and women and guarantee that they receive the required assistance in a timely manner. To obtain the vital information on the gender dynamics of the disaster and its consequences, they have been conducting quick gender assessments and making the data accessible to all involved in the relief efforts. In order to guarantee essential life-saving aid, such as psychological support, dignity kits, PEP kits, emergency aid, trauma treatment, and more, they have also been collaborating with a number of partners, groups, and other UN agencies (UN Women, 2023).In a similar vein, the United Nations International Organization for Migration (IOM, 2024) stated that it has been working with its partners to provide vital life-saving aid to lessen the worsening humanitarian situation in and around Sudan. Continuous updates on population movement, including cross-border mobility and displacement in South Sudan, Ethiopia, the Central African Republic, and Chad, are provided by the IOM’s Displacement Tracking Matrix (DTM). In addition, the International Medical Corps has been offering protective services, water, sanitation, and hygiene (WASH), mental health and psychological support (MHPSS), and medical facilities. The organization has initiated a regional response to the increasing humanitarian needs of internally displaced people. IDPs have also received assistance from the International Rescue Committee (IRC) in the form of programs for economic empowerment, water, sanitation, hygiene, and health and nutrition. The aforementioned interventions make it clear that the humanitarian situation is getting out of control. This could be the result of a lack of political will or a well-defined strategy to deal with the disruption. Remembering that the therapies’ effects are still being felt is crucial.

Conclusion and Recommendations

            It has been shown that the humanitarian needs of those affected by Sudan’s political upheaval are made worse by foreign apathy and inaction. Sudanese people are gradually losing faith in the outside world. The world’s indifference and lack of focus are due to the Israeli-Palestinian conflict, which has dominated international news headlines. The essay calls for the quick use of virtual reality and augmented reality in the rehabilitation and reintegration of Sudanese crisis victims in order to remove evident duplications and challenges in managing the situation that jeopardise the victims’ humanitarian needs. Given the dangerous nature of the situation, prompt adoption of this technology can significantly reduce the humanitarian needs of the victims and the aftermath of the battle. The best way to do this is for the UN High Commissioner for Refugees and other pertinent parties to use augmented reality and virtual reality animation and visuals in the victims’ care.
The integration of virtual reality and augmented reality in the management of the victims will have a major impact on Sudan’s political situation by reconstructing the psychological traumas of the victims, redesigning the lives of the mentally disturbed victims, and upskilling them. Ajah, Nnam, Ajah, Ngozi-Idemili, Onyejegbu, and Agboti (2021) claim that by unintentionally rearranging their cognitive processes, the victims are cultured by the technology. Incorporating virtual and augmented reality into the crisis would also assist the victims in reorganising and reconstructing their thought processes so they can take advantage of opportunities and conform to social norms. With the use of technology, the victims might gain new skills and experiences that would enable them to engage in more economic activity. This aids in the sufferers’ successful life reconstruction.

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