International Journal of Interactive Mobile Technologies (iJIM) – eISSN: 1865-7923 – Vol. 15, No. 08, 2021 Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety in Students https://doi.org/10.3991/ijim.v15i08.18627 Maruf Ahmed Tamal (*), Rabia Akter Daffodil International University, Dhaka, Bangladesh tamal15-5620@diu.edu.bd Syed Akhter Hossain University of Liberal Arts Bangladesh, Dhaka, Bangladesh Karim Mohammed Rezaul Wrexham Glyndwr University, Wales, United Kingdom Abstract—Mathematics Anxiety (MA) is a pessimistic emotional attitude towards math that negatively affects mathematics learning. Due to its adverse impacts on students, assessing Mathematics Anxiety (MA) in early-stage has become a burning need over time. Generally, the existing measures of assessing MA adopt primitive questionnaires, and unweighted rating scale based ap- proaches designed for students’ particular age range. As a consequence, this type of scale is not sufficient enough to use widely. To bridge this gap, consid- ering 839 students, the present study has proposed a Weighted Scoring Based Mathematics Anxiety Rating Scale (WSB-MARS). The reliability and validity of the WSB-MARS were ensured by high item-internal consistency, 1-week test-retest reliability, and the expert panel (validity). The study’s overall find- ings suggest that WSB-MARS is a reliable, valid, generalized scale to assess the severity level of mathematics anxiety in students. Besides, the proposed scale could be implemented as a mobile application system that may help teach- ers/guardians recognize the effective intervention techniques for alleviating mathematics anxiety. Keywords—Mathematics anxiety, mathematics anxiety rating scale, math learning, assessment 1 Introduction Mathematics is an essential cognitive skill not only for academic success but also for effective day-to-day functioning. Math is fundamental to a child’s development & communication skills in later life. It stimulates the brain and improves analytical and problem-solving abilities. As a consequence, mathematics is considered to be the foundation of science and other academic areas. As well as math is a strong predictor for later academic success in school. Despite having significance, many students show a negative attitude towards math due to Mathematics Anxiety (MA). Mathematics 18 http://www.i-jim.org Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… anxiety is a particular form of anxiety disorder that causes reluctance in learning and practicing math. It is a feeling of discomfort, apprehension, or fear that interferes with math performance and achievement [1]. At present, many students worldwide are suffering from MA, which adversely impacts their academic excellence, employabil- ity, and career progression. Because of its pandemic nature in students, this issue has received increasing attention from scholars in recent years. Generally, students begin to face an MA at elementary school, which gradually increases to intermediate and tertiary levels. Previous findings revealed that individuals with math anxiety show more brain activation in brain regions involved with negative emotions and less brain activation in brain regions involved with mathematical thinking [2]. These negative emotions create significant fear among students, encouraging them to avoid mathe- matical activities [3] and math-related careers [4]. On the other hand, this math avoidance leads students to low academic perfor- mance [5] and achievements [6]. As a result, MA is considered a substantial barrier to mathematical learning and is thought to hinder students’ engagement and proficiency in metacognitive processes [7]. So, academicians are trying to figure out appropriate ways to overcome MA so that students can engage in math, achieve a good learning experience, and pursue a future math-oriented career. Generally, two types of approaches are followed to overcome MA: (i) preventative control and (ii) detective control. In preventive control, various cognitive tools [8], [9], [10], and effective learning approaches [11-15] are followed that help students to learn Math with fun and realistic experiences rather than only theoretical exercises. These approaches increase students’ attention to math and reduce the likelihood of math anxiety. On the other hand, detective controls are designed to identify the inten- sity of Mathematics Anxiety, and based on the severity; an effective remedial process is provided to overcome it. Several studies were found where scholars proposed vari- ous scales to assess and measure the severity level of MA. Among them, 98-items based MARS [16] is considered a very trusted and widely accepted measure for diag- nosing MA. The reliability of MARS was ensured by test-retest (α = 0.85) and inter- nal consistency reliability (α = 0.97). However, the main drawback of the MARS is that it takes a long administrative time to complete. Consequently, the study [17] proposed a shorter version of MARS with 30-items whose primary purpose was to reduce the administrative time by keeping the validity and reliability the same as the original 98-items MARS. Later, in [18], 9-items based Abbreviated Math Anxiety Scale (AMAS) was introduced, which claimed a more correct and parsimonious approach to assess MA. Because of its fewer items and higher reliability, AMAS has become popular to asses MA based on psychometric properties. At the same time, several translated [19-20], and researchers commonly use modified [21] versions of AMAS. As the majority of measures of MA are de- signed and implemented for adults and adolescents, in [23], researchers proposed a 19-items based Children’s Mathematics Anxiety Scale UK (CMAS-UK), which was specially developed for children (Age range: 4-7) of the UK. Although there are several scales outside, no significant structural changes have been observed. All these scales are mainly psychometric measurement of behavioral attitudes where students specify their degree (generally 1 to 5, where one means less iJIM ‒ Vol. 15, No. 08, 2021 19 Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… math-anxious and five means extremely math-anxious) of agreement or disagreement for a set of statements (items) and then sum up all the values where high scores indi- cate high Mathematics anxiousness. The key drawback of these existing scales is that the items (factors of MA) are considered equally important to assess MA. However, in reality, each item does not play an equal role in evaluating mathematics anxiety. To bridge this gap, the present study has proposed an effective detective control which identifies the severity level of Mathematics Anxiety of students more accurately. The purpose of the current study can be summarized as follows: • Identifying the underlying factors of Mathematics Anxiety • Categorizing the factors according to importance • Introducing an effective mathematics anxiety rating scale called WSB-MARS • Ensuring the reliability and validity of WSB-MARS • Presenting a mobile application wireframe based on WSB-MARS The rest of the study is arranged in the following way: in section 2, we discussed the methodological part. In section 3, we presented our proposed mathematics anxiety rating scale called WSB-MARS. In section 4, we explained the reliability and validity of WSB-MARS. In section 5, we have introduced a mobile application wireframe based on WSB-MARS. Lastly, in section 6, we discussed the overall study results and concluded with potential future work in this area. 2 Research Methodology The methodology of the current study is split into several sub-sections for better understanding. In 2.1, we briefly outlined the data collection procedures. In 2.2, we discussed how the data set was pre-processed to eliminate conflicting data, and final- ly, in 2.3, we showed the reliability of our survey instrument. 2.1 Participants & primary data collection procedures The present study has followed both qualitative and quantitative approaches to draw a meaningful research conclusion. At the initial stage, significant background work was conducted to identify the critical factors of mathematics anxiety. After find- ing out the responsible factors, all these factors were grouped into seven categories. Based on those findings, a survey (see Fig.1) was designed and distributed (between December 2019 and February 2020) to different class level students of 13 institutions (Level: primary, secondary & tertiary) in Bangladesh. The survey has consisted of 16 self-constructed questionnaires (16-items) that describe internal, external, and cogni- tive symptoms related to students’ mathematics anxiety (see Fig.1). Among 16 ques- tionnaires/items, the first 15 items are based on a 4-point Likert scale, which is used to identify the severity level of mathematics anxiety of an individual student (Severity Range: 0 to 3), and the 16th item represents whether a student is math-anxious or not (Range: 0 and 1). This 16th item is included only for determining the importance of the other 15 items (see details in section 3). A total of 1500 sampled of survey were 20 http://www.i-jim.org Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… distributed online and offline, and 871 responses were gathered (Male = 557 and Fe- male = 314). The sample consisted of 147 primary level students (16.89%), 331 sec- ondary level students (38%), and 393 tertiary level students (45.12%). The age range of the participants was 7 to 25. Fig. 1. Survey details 2.2 Data pre-processing This primary data in this study was collected through both online and field surveys, which were then combined and used as an aggregate dataset. To get reliable and pre- cise measurement, the aggregated dataset was fully preprocessed. We found 32 ab- normal responses where seven records were irrelevant (i.e., responders added infor- mation that was not connected to the study), 16 records were incomplete (i.e., re- sponders did not respond to all questionaries), and nine records were inconsistent and redundant (i.e., same responders responded both online and field survey with different answers). So, we have removed all those responses to get a more efficient result. After performing data pre-processing, 839 valid observations were selected for the next procedures. 2.3 Reliability of the survey instrument (MARS-S) As illustrated above, the present study’s observations were collected through a sur- vey called MARS-S (see Fig.1), which consists of 16-items. It needs to be ensured that MARS-S can reliably fulfill the purpose of the study. Consequently, the reliabil- iJIM ‒ Vol. 15, No. 08, 2021 21 Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… ity of the MARS-S was estimated by Cronbach’s alpha (α) that measures the internal consistency of a group of items [see equation (i)]. 𝛼 = !" ̅ $ &'(!)*)"̅ ( 1) Here, α = Cronbach’s alpha, 𝑁= number of items, 𝑐̅ = average inter-item covari- ance, 𝑣 + = average variance. Findings show that Cronbach’s alpha of MARS-S is α = .93, which indicates a high internal consistency of 16-items. The inter-item correlation matrix of MARS-S also shows positive scores, which indicates those 16-items are working as a group to fulfill the goal without any contrast (see Table 1.). Table 1. Inter-item correlation matrix I1 I2 I3 I4 I5 I6 I7 I8 I9 I10 I11 I12 I13 I14 I15 I16 I1 1.00 I2 .577 1.00 I3 .299 .207 1.00 I4 .753 .582 .344 1.00 I5 .497 .437 .257 .478 1.00 I6 .636 .532 .367 .681 .511 1.00 I7 .627 .526 .301 .671 .414 .665 1.00 I8 .662 .527 .300 .666 .430 .622 .650 1.00 I9 .424 .354 .223 .483 .374 .469 .409 .421 1.00 I10 .480 .531 .164 .419 .388 .416 .447 .472 .282 1.00 I11 .545 .558 .181 .564 .364 .514 .573 .561 .350 .494 1.00 I12 .360 .435 .114 .306 .329 .354 .359 .345 .304 .473 .392 1.00 I13 .582 .493 .227 .577 .532 .588 .560 .518 .421 .461 .525 .439 1.00 I14 .454 .474 .204 .461 .433 .468 .482 .451 .404 .452 .450 .541 .576 1.00 I15 .454 .503 .206 .468 .387 .482 .488 .450 .453 .483 .452 .545 .503 .635 1.00 I16 .743 .619 .363 .728 .503 .716 .721 .769 .465 .530 .612 .410 .586 .541 .553 1.0 3 Research Results The core structure of WSB-MARS is illustrated in this section. In section 3.1, we demonstrated how to determine the items’ weight based on their role in creating an MA. Lastly, in section 3.2, we discussed briefly how our proposed scale (WSB- MARS) works. 3.1 Determining the weight of the items based on importance In MARS-S (see Fig.1), the first 15 items are used to identify the severity level of mathematics anxiety, and the 16th item represents whether a student is math-anxious or not. The primary purpose of the 16th item is to help (as a target variable) identify the importance of the first 15 items in terms of diagnosing mathematics anxiety. In this current study, we used SelectKBest (Python Class) and a function called chi- 22 http://www.i-jim.org Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… squared to select items according to their highest scores. The column “Importance of Items (IOI)” of table 2 represents the scores of the first 15 items against the target variable (16th item). At the same time, the weighted point of the first 15 items (ac- cording to their degree) was calculated in column “Weighted Point (WP) = UP*IOI” (see Table 2). Table 2. Scoring of items according to the importance I. No. Importance of Items (IOI) Unweighted Point (UP) Weighted Point (WP) = UP*IOI Never Rarely Sometimes Very often Never Rarely Sometimes Very often 1 292.19 0 1 2 3 0 292.19 584.38 876.57 2 333.21 0 1 2 3 0 333.21 666.42 999.63 3 71.96 0 1 2 3 0 71.96 143.92 215.88 4 308.57 0 1 2 3 0 308.57 617.14 925.71 5 88.20 0 1 2 3 0 88.2 176.4 264.6 6 313.22 0 1 2 3 0 313.22 626.44 939.66 7 377.84 0 1 2 3 0 377.84 755.68 1133.52 8 443.81 0 1 2 3 0 443.81 887.62 1331.43 9 112.49 0 1 2 3 0 112.49 224.98 337.47 10 187.16 0 1 2 3 0 187.16 374.32 561.48 11 359.94 0 1 2 3 0 359.94 719.88 1079.82 12 110.44 0 1 2 3 0 110.44 220.88 331.32 13 145.89 0 1 2 3 0 145.89 291.78 437.67 14 155.51 0 1 2 3 0 155.51 311.02 466.53 15 193.17 0 1 2 3 0 193.17 386.34 579.51 3.2 Weighted scoring based rating scale After calculating the Weighted Point (WP) of each item (see Table 2), the cumula- tive value of all the WPs represents the severity score of the mathematical anxieties of a particular student. (See step 3, Algorithm 1). According to our proposed Weighted Scoring Based Mathematics Anxiety Rating Scale (WSB-MARS), the maximum or highest possible severity score can be 10480.8, and the lowest or minimum possible severity score can be 0. A higher severity score indicates higher mathematics anxiety, and a lower severity score indicates students’ lower mathematics anxiety. For better understanding, the overall severity score has been divided into 4 stages e.g., NORMAL (0 <= severity_score <= 2,620), MILD (2,620 < severity_score <= 5,240), MODERATE (5,240 < severity_score <= 7,860) and SEVERE (7,860 < severi- ty_score < 10481) (see step 4, Algorithm 1). iJIM ‒ Vol. 15, No. 08, 2021 23 Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… Algorithm 1. Weighted Scoring Based Rating Scale Input: Unweighted Points (UP) & Importance of Items (IOI) Output: Severity score of Mathematics Anxiety Step 1: X {1, 2, 3, 4, 5……...15} = Unweighted Points of 15 items Step 2: Y {1, 2, 3, 4, 5……...15} = Importance of 15 items Step 3: 𝒔𝒆𝒗𝒆𝒓𝒊𝒕𝒚_𝒔𝒄𝒐𝒓𝒆 = 6 𝑋[𝑖] ∗ 𝑌[𝑖] ,-*. /-* [Severity score range: Min: 0 to Max: 10480.8] Step 4: if (severity_score>= 0 && severity_score<= 2,620) Return “Severity Level = NORMAL” else if (severity_score>2,620 && severity_score<= 5,240) Return “Severity Level = MILD” else if (severity_score>5,240 && severity_score<= 7,860) Return “Severity Level = MODERATE” else if (severity_score>7,860 && severity_score< 10481) Return “Severity Level = SEVERE” 4 Reliability and Validity of the Proposed Scale (WSB-MARS) 4.1 Reliability The reliability of our proposed scale WSB-MARS is ensured by the 1-week test- retest reliability coefficient (see Fig.2). It’s a measure of the reliability achieved by performing the same test twice in a group of people over a period of time [22]. About 150 students from different schools (primary, secondary, and tertiary) took part in the test twice a week. The mean of the first test result (severity score) was 4921.10 (SD = 2223.5) and the second test result was 4984.37 (SD = 2011.4). Pearson’s correlation coefficient (see formula ii) between the two test scores was 0.968. The overall finding confirms that WSB-MARS can reliably measure the Mathematics Anxiety of stu- dents. 𝑟 = ∑(1! )1̅)(2! )23) 4 ∑(1! )1̅)# ∑(2! )23)# (2) Here, r = Pearson’s correlation coefficient, 𝑥/ = scores of the first test, �̅� = mean of the first test scores, 𝑦/ = scores of the second test, 𝑦A = mean of the scores of the sec- ond test. 24 http://www.i-jim.org Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… Fig. 2. Test-Retest reliability of WSB-MARS 4.2 Validity The validity of the proposed scale (WSB-MARS) was ensured by the consultancy of the expert panel (n = 6) based on the following metrics: (i) Reliability of the survey instrument, (ii) Quality of the factors of mathematics anxiety, (iii) The ability of WSB-MARS to measure the severity level of mathematics anxiety (iv) Simplicity and (v) Administrative time to take a test. Table 3 provides the validity details of WSB- MARS. Findings indicate that WSB-MARS is considered a valid instrument to assess MA. Table 3. Validity test details Expert Metric (i) Metric (ii) Metric (iii) Metric (iv) Metric (v) Good Ok poor Good Ok Poor Good Ok Poor Good Ok Poor Good Ok Poor 1 ü ü ü ü ü 2 ü ü ü ü ü 3 ü ü ü ü ü 4 ü ü ü ü ü 5 ü ü ü ü ü 6 ü ü ü ü ü 5 A Mobile Application Framework Based on WSB-MARS Generally, existing mathematics anxiety (MA) measures are used in education, re- search, psychology, clinical studies, etc., where researchers and academicians perform all the tasks manually rather than using an automated process. Consequently, it takes much time, effort, and money to complete the whole procedure. To overcome this gap, our proposed scale could be used as a mobile app to help teachers measure the severity level more quickly and take appropriate steps to reduce it. Fig. 3 represents the proposed mobile application wireframe, which highlights the functionalities and iJIM ‒ Vol. 15, No. 08, 2021 25 Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… vital steps. Through this application, a teacher can efficiently perform several activi- ties. Initially, a teacher needs to register himself/ herself with the necessary infor- mation to get into the apps. After successful registration, he/she will be able to log in and begin the next steps. After a successful login, he/she will be able to create a new test, set questions with additional information (options, default values, time limits, etc.), and assign the test to the target students. By default, there will be 15 questions from MARS-S. The teacher will determine the weight of each question, generate the rest report, and recommend an effective remedial program for a particular student. At the same time, a teacher will warn the students’ guardians about their child’s condi- tion. On the other hand, students can also do different things, including self- registration, performing the assigned test, taking notes, checking remedial programs via this application. Fig. 3. Mobile application wireframe 26 http://www.i-jim.org Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… 6 Discussion and Conclusion Mathematics Anxiety (MA) has become a global concern nowadays. Early identifi- cation of the severity level of MA can reduce its negative impacts to a certain degree. Generally, two approaches are followed to alleviate Mathematics Anxiety: (i) preven- tative approach and (ii) detective approach. In this study, we introduced a detective instrument called Weighted Scoring Based Mathematics Anxiety Rating Scale (WSB- MARS) that can assess the severity level of Mathematics Anxiety among students. The reliability and validity of the proposed WSB-MARS were ensured by item- internal consistency (Cronbach’s alpha: α =.93), test-retest reliability: r = .968, and consultancy of an expert panel, respectively. Since WSB-MARS has 15 items, it takes a short administrative time to complete a test. This makes WSB-MARS easy to use compared to existing scales. Table 4 represents a comparative analysis between our proposed scale and the existing scales. Findings show that existing scales were de- signed for a particular age range of students. On the other hand, WSB-MARS is con- structed based on primary, secondary & tertiary level students. Table 4. Comparative discussion Scale Total Items Targeted Students/Age Reliability Score Sample Size (N) Ref. MARS 98 Tertiary Level 0.85 (test-retest) 397 (80% Female, 20% Male) [12] MARS (Short Version) 30 Age range: 17 -26 0.90 (test -retest) 124 (63 Females, 61 Males) [13] AMAS 9 Ave. age: 19.6 0.85 (test-retest) 1,239 (729 Females, 510 Males) [14] AMAS (Italian Version) 9 Primary Level 0.83 (test - retest) 1013 (51% Male, 49% Female) [15] AMAS-G 9 Age range: 18 - 35 0.82 (test -retest) 221 (221 Females, 0 Male) [16] mAMAS 9 Age range: 8 - 13 0.85 (test-retest) 1746 (882 Males, 864 Females) [17] CMAS - UK 19 Age range: 4 - 7 N/A 163 (90 Males, 73 females) [22] WSB -MARS 15 Age range: 7 - 25 (primary, secondary & tertiary) 0.968 (test - retest) 871 (557 Males, 314 Females). Our Proposed Scale The proposed scale (WSB-MARS) could be implemented as a mobile application that may help teachers/guardians find out the root of students’ mathematics anxiety and its level of severity. As WSB-MARS is a reliable, valid, and new approach to assess the severity level of mathematics anxiety in students, it can be useful in the research and education field [24]. However, some limitations are still observed, like less primary data and preliminary validity tests. On the other hand, WSB-MARS is solely based on information from Bangladeshi students. As a consequence, effective- ness may vary outside Bangladesh. So, in the future, we expect to eliminate the above limitations and increase its effectiveness. iJIM ‒ Vol. 15, No. 08, 2021 27 Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… 7 Acknowledgement The data collection process in this study was very challenging. However, the teachers’ and students’ cumulative effort from different level institutions in Bangla- desh made this happen. 8 References [1] M. A. Klados, E. Paraskevopoulos, N. Pandria, and P. D. 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Sheffield, T. Hunt, and S. Fitton-Wilde, "Further development of the Children's Mathematics Anxiety Scale UK (CMAS-UK) for ages 4-7 years", Educa- tion-al Studies in Mathematics, vol. 100, no. 3, pp. 231-249, 2018. https://doi.org/10.1007/ s10649-018-9860-1 [24] Papadakis, St. Robots and Robotics Kits for Early Childhood and First School Age. Inter- na-tional Journal of Interactive Mobile Technologies (iJIM), 14 (18), 34-56, 2020. https://doi.org/10.3991/ijim.v14i18.16631 9 Authors Maruf Ahmed Tamal is currently working as a lecturer & Head of Quality assurance of NIET.UK. He also works as an associate researcher of the Bangladesh Digital Education Re- search Ltd., Gulshan 1, Dhaka, Bangladesh. He received his B.Sc. degree in Computer Science and Engineering from Daffodil International University, Dhaka, Bangladesh, in 2019. His primary area of expertise is machine learning and data mining-based knowledge discovery. He also pursues interests in ICT based Pedagogy. iJIM ‒ Vol. 15, No. 08, 2021 29 Paper—A Weighted Scoring Based Rating Scale to Identify the Severity Level of Mathematics Anxiety… Rabia Akter is a researcher who received her B.Sc. degree in Computer Science and Engi- neering from Daffodil International University, Dhaka, Bangladesh, in 2019. His primary areas of expertise are Human-Computer Interaction (HCI), Data mining and the Internet of Things (IoT). He also pursues interests in the education field. Professor Syed Akhter Hossain is currently the Head, Department of Computer Science and Engineering at University of Liberal Arts Bangladesh, one of the top leading digital univer- sity of Bangladesh from 1st January 2021. Prior to joining ULAB, Professor Hossain served as the Professor and Head of the Department of Computer Science and Engineering at Daffodil International University from 2010 to December, 2020. Professor Hossain obtained B.Sc. and M.Sc. in Applied Physics and Electronics with Gold medal and distinction and Ph.D. in Com- puter Science and Engineering with a post-doctoral research in automation and artificial intelli- gence. As Erasmus Mundus post-doctoral fellow he contributed in the area of Informatics and Industrial Engineering with University Lumiere Lyon 2 in France. He has more than 30 years of working experience in industry, education, research and training. He is actively involved in research guidance/ research projects/ research collaborations with Institutes/ Industries and has more than 250 publications/ presentations and his work is listed in ACM, DBLP, IEEE Explore and other research databases. He works closely with the ICT Division of the Ministry of Post, Telecommunication and IT of the Government of the Peoples Republic of Bangladesh. He received several national and international awards for his outstanding contribution in ICT edu- cation, innovative projects for the visually impaired people. He also received other International awards for his scholastic works specially for the contribution of machine translator for Bangla Braille used by the visually impaired society. He received best researcher award in the year 2019 from the university. His current research interests includes Machine Learning and AI with Natural Language Processing. Karim Mohammed Rezaul was awarded a PhD degree in Computing and Communications Technology from North East Wales Institute (NEWI) of Higher Education (presently Wrexham Glyndŵr University), University of Wales, UK in October 2007. He received his BSc degree in the field of Naval Architecture and Marine Engineering from Bangladesh University of Engi- neering and Technology (BUET), Dhaka in 1998 and, MSc degree in Marine Technology from Norwegian University of Science and Technology (NTNU), Trondheim, Norway in 2001. Presently, he is a Professor of Computing & Communications Technology at Wrexham Glyndwr University, UK and Adjunct Professor in Management at IPE Management School Paris, France. He is also a Professor of Computer Science & Engineering (CSE) at Sonargaon University (SU), Dhaka, Bangladesh. Since 2002, Prof. Karim has been working as an Academ- ic advisor and Programme director at various International colleges and universities in the UK and Bangladesh. Prof. Karim is an author of numerous Scientific and Business articles (Schol- arly & Refereed publications) which include book, book chapters, journals and International conference proceedings. He is an editor of several international journals and a member of the Technical Program Committee (TPC) of multiple International conferences. His research inter- ests include IS Design and Development; ICT-based Pedagogy; Internet of Things (IoT); Arti- ficial Intelligence (AI); Fractals and Nanotechnology; Networking - Traffic Engineering, Quali- ty of Service (QoS) Control, Traffic modelling & simulation etc.; Distributed DBMS; Information Security; Business Intelligence; E-Business/E-commerce; ICT Project Manage- ment; Computing. Article submitted 2020-09-16. Resubmitted 2021-01-08. Final acceptance 2021-01-08. Final version published as submitted by the authors. 30 http://www.i-jim.org