Biology Students' Future Skills in Artificial Intelligence Applications from the Perspective of Science Department Lecturers

Abstract

  This research aims to identify the extent to which life sciences students possess future skills related to artificial intelligence applications, from the perspective of faculty members in the science department, by activating the role of higher education institutions in achieving this. Universities bear a significant responsibility in addressing cognitive developments in light of technological advancements and their impact on societies in general and the educational system in particular.

  The research adopted a descriptive-analytical approach, focusing on determining the level of availability of future skills related to artificial intelligence applications among life sciences students in the science department at the University of Babylon, College of Basic Education, for the academic year 2025/2026. This was achieved by surveying the perspectives of faculty members in the science department where the life sciences students are enrolled.

  To achieve the research objective, the researcher developed a future skills scale based on artificial intelligence applications. This scale was based on the skills included in the scale developed in the study by Baawain (2022), which comprised 14 skills (basic, applied, and technical) consisting of 32 items distributed across three main future skills categories:

1- Basic skills (11 items).

2- Applied skills (11 items).

3- Technical skills (10 items).

  The questionnaire was reviewed by experts, and its validity and reliability coefficients were calculated. The research sample consisted of 46 male and female faculty members in the Department of Science. To determine the availability of future skills among life sciences students, based on artificial intelligence applications, the weighted mean and percentage were calculated for the questionnaire items after distributing it to the research sample, and the frequencies for each item and domain were calculated.

  The results showed that most of the future skills, according to artificial intelligence applications for life sciences students, were available to varying degrees based on the responses of the research sample of faculty members of both genders. Some items received average ratings, especially those related to basic skills, which require more extensive attention. The results also showed a very slight similarity in the faculty members' viewpoints based on gender regarding the evaluation of the questionnaire items and its main components. Male faculty members' ratings were higher than those of female faculty members for all items. In light of the research findings, a number of conclusions, recommendations, and suggestions were formulated.