Empowering Qualitative Research Methods in Education with Artificial Intelligence

Artificial Intelligence is one of the fastest growing disciplines, disrupting many sectors. Originally mainly for computer scientists and engineers, it has been expanding its horizons and empowering many other disciplines contributing to the development of many novel applications in many sectors. These include medicine and health care, business and finance, psychology and neuroscience, physics and biology to mention a few. However, one of the disciplines in which artificial intelligence has not been fully explored and exploited yet is education. In this discipline, many research methods are employed by scholars, lecturers and practitioners to investigate the impact of different instructional approaches on learning and to understand the ways skills and knowledge are acquired by learners. One of these is qualitative research, a scientific method grounded in observations that manipulates and analyses non-numerical data. It focuses on seeking answers to why and how a particular observed phenomenon occurs rather than on its occurrences. This study aims to explore and discuss the impact of artificial intelligence on qualitative research methods. In particular, it focuses on how artificial intelligence have empowered qualitative research methods so far, and how it can be used in education for enhancing teaching and learning

Automated detection of Barrett’s esophagus using endoscopic images: a survey

Barrett’s Esophagus (BE) is the predominant sign leading to esophageal adenocarcinoma (EAC) which is cancerous. Esophageal cancer has shown a very low survival rate in the last decade. Early detection of BE, and monitoring cells development is an effective way to control the progression of the cell transform into EAC in the lining of the esophagus. The examination of BE is done by using one the different endoscopy tools, the appearance of endoscopic imaging techniques created the opportunity for computer-aided detection (CAD) systems to develop more frequently. Such methods intend to help physicians by identifying abnormalities more accurately. The purpose of this survey is to discuss advances in the development of BE CAD systems as it has only started to grab attention recently. Starting with a brief introduction about endoscopy modalities used for esophageal examination. Then focusing on detection methods lately developed for BE detection. Remaining challenges are mentioned and some directions for future research are given