Education is one of the basic needs that every child should have. Information communication technology has a significant influence on special needs children’s schooling. Instead of considering learning a difficult chore, the adoption of measures such as ICT can simplify it and make inclusive education a reality. Aim: This current systematic literature review aims to determine the extent of ICT adoptions in special education scenarios. Method: This paper examined pertinent literature on ICT in special education in the period 2000 to 2023. The key articles extracted through keyword search were gathered from databases indexed in Web of Science and Scopus. The collected data were then screened using a VOS viewer for the most relevant information. From the web of Science, 31 articles were found to have connections with one another while the same process when applied to the Scopus database, helped obtain 8 articles. Results: A total of 39 articles fulfilled the search inclusion criteria of minimum two keyword occurrences. These articles were all written in English and published between 2000 and 2023. The in-depth analysis of all these articles was performed along three broad themes, viz., availability of SEN based ICTs and their impact on children with disabilities, quality of available ICT integrated curriculum for SEN and the challenges in promoting ICTs for inclusive education. Conclusions: The paper concludes that ICT integration in special education would make learning easier for children with disabilities when compared to learning using traditional methods. Implications: The paper pinpoints significant limitations in ICT use found in existing literature and the lack of it to support inclusive education. The authors make recommendations for improved ICT integrated curriculum to improve inclusivity.

The growth of mobile Internet has facilitated access to information by minimizing geographical barriers. For this reason, this paper forecasts the number of users, incomes, and traffic for operators with the most significant penetration in the mobile internet market in Colombia to analyze their market growth. For the forecast, the convolutional neural network (CNN) technique is used, combined with the recurrent neural network (RNN), long short-term memory network (LSTM), and gated recurrent unit (GRU) techniques. The CNN training data corresponds to the last twelve years. The results currently show a high concentration in the market since a company has a large part of the market; however, the forecasts show a decrease in its users and revenues and the growth of part of the competition. It is also concluded that the technique with the most precision in the forecasts is CNN-GRU.