The recent years have witnessed an increasing importance of machine translation systems due to the prolific production on online texts in different disciplines and furthermore, the inability of traditional translation methods in addressing translation needs all over the world. It is even argued that training on translation tools should be integrated into translation pedagogies and ultimately, courses should be provided for students and professionals. In spite of the effectiveness of translation tools and systems in providing solutions in relation to different disciplines and text genres, the usability and reliability of such systems in terms of literary texts, however, is still highly controversial. Many critics and educators still underestimate the usefulness of the machine translation systems in literature, which could be partially attributed to the unique nature of the language of the literary texts. The issue has its pedagogical implications to translation instruction due to the needs to integrate emerging technologies in teaching and learning practices. For proper use of translation technologies in educational contexts, these need to be well evaluated. For this purpose, this study evaluates the usefulness of applying machine translation systems to literature with the purpose of identifying the challenges that may have negative impacts on the reliability of machine translation systems. In order to do this this, two translation systems are selected, namely, Google Translate and Q Translate. By way of illustration, the study is based on a corpus of two English short stories. The study is based on two prose fiction texts. The first is J. K. Rowling’s novel Harry Potter and the Philosopher’s Stone. The second is Edgar Allan Poe’s short story The Black Cat. Automatic translations generated by the two machine translation systems were compared to human made Arabic translations with the purpose of identifying the problems within these translations. Results indicate that different lexical, structural, and pragmatic errors are encountered by users which negatively impact the reliability of these translations. Educators and translation instructors need to reflect on the challenges of machine translation systems in relation to literature. Software developers need also to address the problems faced by users and students in the translation from and into the Arabic language.

In the face of the challenges of the Digital Age and the outbreak of the pandemic COVID-19 which have changed higher education institutions remarkably, universities are urgently required to speed up their digitalization initiatives and cope up with the global digital developments to survive. For the successful implementation of digital transformation, however, data governance should be considered. Despite the extensive literature on data governance and digital transformation, there is no focus on the issue in the Saudi Higher Education institutions. In the face of this, the current study investigates data governance policies and practices in the Saudi Universities. This study is built on a case study design. Nine universities in Saudi Arabia were selected for the purpose of the study. These include public, community, and private universities that make up the Higher Education system in Saudi Arabia. For data collection purposes, three methods were selected. These were the survey, focus group discussions and in-depth interviews. The findings of this study indicate that data governance is an effective tool in the implementation of digital transformation processes in higher education institutions and thus should be embedded into strategies of the universities for using digital technologies in appropriate manners. Good data governance practices are required for smooth and effective digital transformation. Universities are required to create an effective functional team for the data governance tasks, develop an internal audit of data governance, follow-up the regulatory compliance procedures, define the priorities of data governance activities, provide frequent data governance training for employees and faculty members, set enforcement and follow-up standards, and conduct frequent assessments of data governance plans and policies. Although the study is limited to the Saudi universities, results and implications of this study can be a useful reference to choose effective data governance practices that can be successfully adopted and implemented to effectively manage critical information and use it to transform their day-to-day operations.

This study addresses the issue of integrating mobile-assisted language learning (MALL) systems into L2 reading instruction in the Saudi secondary schools in order to improve the reading comprehension skills of struggling EFL students. The focus is to find out whether students’ language performance is accelerated by using MALL together with teacher instruction versus conventional instruction alone. In order to assess the effectiveness of MALL systems and activities in improving reading comprehension skills in EFL contexts, an experimental study was carried out where 120 participants of grade ten students in four public secondary school of Riyadh District in Saudi Arabia were randomly divided into two groups: experiment and control. Reading skills of the participants’ were measured by pre-test and post-test by a panel of three national experts. The comparison between the experimental group and the control group pinpoint that MALL materials and systems improve reading comprehension skill among EFL students. The findings indicate clearly that there was a significant difference between MALL users and nonusers in favour of the experimental group (p < .05). It can be then generalized that MALL systems and applications in general provide a motivating learning environment for teaching reading which has its positive implications on improving the reading skills of students.

Assessment is an inseparable part of teaching and learning, and it helps teachers and students to modify their teaching and learning processes. One type of assessment is peer assessment (PA), and its effects were examined on developing Iranian EFL learners’ reading comprehension (RC), reading motivation (RM) and vocabulary learning (VL) in this research. To achieve this goal, 60 Iranian EFL students at the intermediate level and with the age range of 18 to 26 years were selected based on a convenience sampling method and divided into two groups: the control group (CG) and experimental group (EG). After that, the groups took the pre-tests of RC, RM, and VL. The EG then was divided into six sub-groups of five, and PA was applied to evaluate their reading and vocabulary performances. The learners in the EG checked their classmates’ performances in peers with the teacher’s help. In the CG class, the participants themselves assessed their own performances after each test with the help of the teacher. After a 15-session treatment, the post-tests of vocabulary, RM, and RC were carried out on both groups. The outcomes of the one-way ANCOVA tests demonstrated that the EG outflanked the CG on the three post-tests of RC, RM, and VL. In fact, the results indicated that using PA generated positive effects on Iranian EFL learners’ RC, RM, and VL. It can be claimed that the PA is a practical technique to improve EFL learners’ language learning. The implications of this research can reduce students’ dependency on teachers and increase their independence in the evaluation process.

The recent years have witnessed the development of numerous approaches to authorship attribution including statistical and linguistic methods. Stylometric authorship attribution, however, remains among the most widely used due to its accuracy and effectiveness. Nevertheless, many authorship problems remain unresolved in terms of Arabic. This can be attributed to different factors including linguistic peculiarities that are not usually considered in standard authorship systems. In the case of Arabic, the morphological features carry unique stylistic features that can be usefully used in testing authorship in controversial texts and writings. The hypothesis is that much of these morphological features are lost due to the execution of stemming. As such, this study is concerned with investigating the effectiveness of stemming in the stylometric applications to authorship attribution in Arabic. In so doing, three Arabic stemmers GOLD stemmer, Khoga stemmer, Light 10 stemmer are used. By way of illustration, a corpus of 2400 news articles written by different 97 authors is designed. To evaluate the effectiveness of stemming, the selected articles (both stemmed and unstemmed texts) are clustered using cluster analysis methods. Comparisons are made between clustering structures based on stemmed and unstemmed datasets. The results indicate that stemming has negative impacts on the accuracy of the clustering performance and thus on the reliability of stylometric authorship testing in Arabic. The peculiar stylistic features of the affixation processes in Arabic can, thus, be usefully used for improving the performance of authorship attribution applications in Arabic. It can be finally concluded that stemming is not effective in the stylometric authorship applications in Arabic.