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    <title>American Journal of Educational Research</title>
    <link>http://www.sciepub.com/journal/EDUCATION</link>
    <description>American Journal of Educational Research is a peer-reviewed, open access journal that provides rapid publication of articles in all areas of educational research. The goal of this journal is to provide a platform for scientists and academicians all over the world to promote, share, and discuss various new issues and developments in different areas of educational research.</description>
    <dc:publisher>Science and Education Publishing</dc:publisher>
		<dc:language>en</dc:language>
		<dc:rights>2013 Science and Education Publishing Co. Ltd All rights reserved.</dc:rights>
		<prism:publicationName>American Journal of Educational Research</prism:publicationName>
		14
		3
		January 2026
		<prism:copyright>2013 Science and Education Publishing Co. Ltd All rights reserved.</prism:copyright>
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<rdf:li resource="http://pubs.sciepub.com/education/14/3/3"/>
<rdf:li resource="http://pubs.sciepub.com/education/14/3/4"/>
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  <item rdf:about="http://pubs.sciepub.com/education/14/3/1">
<title>
Evaluation of the Importance Given to the Various Teaching Subjects Within Study Programmes, of the Same or Different Scientific Discipline Departments in Higher Education Institutions: a Criteria-based Approach
</title>
<link>http://pubs.sciepub.com/education/14/3/1</link>
<description>
<![CDATA[The purpose of this article is to describe an updated version of a previous specific study, as well as the creation and implementation of a criteria-based approach that was applied to it. Above all, the goal of this paper is to give necessary additional information and instructions, so that the same criteria-based process, as well as the accompanying methodology, can be easily used by researchers for other related aims regarding Higher Education Institutions (HEIs), after applying appropriate amendments or adjustments.]]>
</description>
<dc:creator>
Chris  Lamprou, Sofia  Papazoglou, Dimitrios  Foteinos, Nikitas  Nomikos, Alina  Terzi, Costas  Mountakis, Kostas Mylonas
</dc:creator>
<dc:date>2026-03-01</dc:date>
<dc:publisher>Science and Education Publishing</dc:publisher>
<prism:publicationDate>2026-03-01</prism:publicationDate>
<prism:number>3</prism:number>
<prism:volume>14</prism:volume>
<prism:startingPage>81</prism:startingPage>
<prism:endingPage>89</prism:endingPage>
<prism:doi>10.12691/education-14-3-1</prism:doi>
</item>
<item rdf:about="http://pubs.sciepub.com/education/14/3/2">
<title>
Acceptability of AI Tools in the Conduct of Research
</title>
<link>http://pubs.sciepub.com/education/14/3/2</link>
<description>
<![CDATA[The rapid growth of Artificial Intelligence (AI) has influenced academic research practices, transforming the ways in which research activities were conducted. The present study examined research scholars’ perceptions of AI tools to understand their effective and ethical integration into academic research. A mixed-method research design was employed, and data were collected from research scholars across different universities in West Bengal using a self-constructed questionnaire administered online. Quantitative data were analyzed descriptively, while qualitative responses provided deeper insights into perceived benefits and concerns related to AI use. The findings indicated that research scholars demonstrated a generally positive perception toward the acceptance and application of AI tools in research, acknowledging their potential to enhance research quality, efficiency, and productivity. However, concerns related to ethics, plagiarism, over-reliance on technology, accuracy of AI-generated content, and data privacy was also reported. The study concluded that although research scholars exhibited favorable attitudes toward AI tools, institutional support, structured training, and clear ethical guidelines were essential to ensure the responsible and effective integration of AI in academic research.]]>
</description>
<dc:creator>
Sutapa  Garai, Dr.  Sarita Anand, Shubha  Sarkar
</dc:creator>
<dc:date>2026-03-02</dc:date>
<dc:publisher>Science and Education Publishing</dc:publisher>
<prism:publicationDate>2026-03-02</prism:publicationDate>
<prism:number>3</prism:number>
<prism:volume>14</prism:volume>
<prism:startingPage>90</prism:startingPage>
<prism:endingPage>95</prism:endingPage>
<prism:doi>10.12691/education-14-3-2</prism:doi>
</item>
<item rdf:about="http://pubs.sciepub.com/education/14/3/3">
<title>
Teachers’ Attitude, Competence, and Challenges in Using Artificial Intelligence in Teaching Secondary Science
</title>
<link>http://pubs.sciepub.com/education/14/3/3</link>
<description>
<![CDATA[This study aimed to assess teachers’ attitudes, perceived competence, and challenges in using AI in teaching secondary science, examining differences based on age, sex, highest educational attainment, years of teaching experience, number of relevant trainings, and specialization. The study was conducted in the different high schools in the District II of Ifugao, Philippines. A quantitative descriptive research design was employed. Data were collected using an adapted questionnaire and analyzed using frequencies and percentages, and mean. Key findings indicated that teachers held a very positive attitude toward AI in science education, recognizing its ability to enhance learning, personalize instruction, and support critical thinking. Teachers perceived competence was examined using three domains: general competence, access to resources, and professional development. Respondents rated themselves <i>very high</i> <i>(very competent)</i> in general competence, demonstrating confidence in understanding AI concepts, integrating AI with traditional teaching methods, and evaluating AI’s effectiveness. Access to AI tools and support was also rated very high, with teachers reporting sufficient availability of software, technical support, and instructional materials. Professional development was rated high; teachers actively sought AI-related learning and perceived training opportunities as available, but the actual receipt, quality, and relevance of training were limited. The most severe challenges identified included concerns about data privacy, reliability of AI-based assessments, ethical issues, institutional policy ambiguity, and keeping up with rapid technological developments. The study recommends an action plan to enhance teachers’ knowledge and understanding of AI and its applications in science education, strengthen skills for integrating AI into lesson planning, instruction, and assessment aligned with MELCs, and promote ethical, responsible, and secure use of AI in compliance with DepEd data privacy and child protection policies.]]>
</description>
<dc:creator>
Marjorie  L. Chinaman, Madeilyn  B. Estacio, Romiro  G. Bautista
</dc:creator>
<dc:date>2026-03-02</dc:date>
<dc:publisher>Science and Education Publishing</dc:publisher>
<prism:publicationDate>2026-03-02</prism:publicationDate>
<prism:number>3</prism:number>
<prism:volume>14</prism:volume>
<prism:startingPage>96</prism:startingPage>
<prism:endingPage>102</prism:endingPage>
<prism:doi>10.12691/education-14-3-3</prism:doi>
</item>
<item rdf:about="http://pubs.sciepub.com/education/14/3/4">
<title>
Effectiveness of Digital Vocabulary Tools on Vocabulary Growth among Senior High School Students in Cagayan de Oro City: Basis for Strategic Educational Planning
</title>
<link>http://pubs.sciepub.com/education/14/3/4</link>
<description>
<![CDATA[Vocabulary development is a critical component of language learning as it directly influences students’ reading comprehension, communication skills, and overall academic performance. Despite national efforts to improve literacy and integrate digital technologies in education, many senior high school students in the Philippines continue to struggle with limited vocabulary knowledge. This study examined the effectiveness of selected digital vocabulary tools—Quizlet, Duolingo, Memrise, and Italki—in improving the vocabulary skills of senior high school students in Cagayan de Oro City and explored how these tools may inform strategic educational planning for vocabulary instruction. The study employed a quasi-experimental pre-test–post-test control group design involving 150 Grade 12 students from six public secondary schools. Participants were divided into four experimental groups, each assigned to a specific digital vocabulary tool, and one control group that received traditional vocabulary instruction. The Vocabulary Levels Test (VLT) was used to measure students’ vocabulary proficiency before and after a four-week intervention period. Quantitative data were analyzed using descriptive statistics, paired-samples t-tests, and one-way ANOVA, while qualitative insights were gathered through student feedback questionnaires and semi-structured interviews with teachers and administrators. Results revealed that all experimental groups demonstrated significant improvement in vocabulary scores from pre-test to post-test. Among the digital tools, Italki produced the highest mean gain, followed closely by Memrise, Quizlet, and Duolingo. Post-test results also showed that students who used digital vocabulary tools achieved significantly higher vocabulary scores than those in the control group. Qualitative findings indicated that students perceived the tools as engaging, interactive, and supportive of vocabulary learning, while teachers and administrators highlighted their potential for enhancing language instruction despite challenges related to internet connectivity and access to devices. The findings suggest that integrating digital vocabulary tools into classroom instruction can significantly enhance students’ vocabulary acquisition and engagement. The study recommends structured integration of digital tools, strengthened teacher training, and improved digital infrastructure to support sustainable implementation. These results provide empirical evidence that can guide curriculum enhancement and strategic educational planning for technology-supported vocabulary instruction in Philippine senior high schools.]]>
</description>
<dc:creator>
Alvin  O. Holoyohoy, Valentina  A. Pallo
</dc:creator>
<dc:date>2026-03-12</dc:date>
<dc:publisher>Science and Education Publishing</dc:publisher>
<prism:publicationDate>2026-03-12</prism:publicationDate>
<prism:number>3</prism:number>
<prism:volume>14</prism:volume>
<prism:startingPage>103</prism:startingPage>
<prism:endingPage>106</prism:endingPage>
<prism:doi>10.12691/education-14-3-4</prism:doi>
</item>
<item rdf:about="http://pubs.sciepub.com/education/14/3/5">
<title>
Integration of a Personalized Generative AI into University Instructional Design: Contributions, Uses, and Conditions for the Effectiveness of Active Learning Methods
</title>
<link>http://pubs.sciepub.com/education/14/3/5</link>
<description>
<![CDATA[The rapid expansion of generative artificial intelligence (AI), particularly large language models (LLMs), is profoundly transforming higher education by enabling the on-demand production of instructional content, learning activities, feedback, and assessment tools. However, recent research indicates that these uses remain largely opportunistic and insufficiently embedded within systematic instructional design processes. This weak integration may compromise constructive alignment between intended learning outcomes, learning activities, and assessment methods, as well as undermine academic integrity. And this article offers a structured synthesis of the contributions, uses, and effectiveness conditions of a personalized generative AI—defined as an AI system configured through stable pedagogical instructions, institutional constraints, and disciplinary frameworks—designed to support active learning approaches in higher education. The study is based on a qualitative documentary analysis of recent international scientific publications (during 2023–2025), complemented by the examination of a university teaching resource used as an empirical case of implementation. The findings highlight three major contributions. First, personalized generative AI can support the entire instructional design cycle, from needs analysis to assessment design, by strengthening pedagogical coherence and constructive alignment. Second, the dominant uses identified primarily concern the design of active learning strategies (flipped classroom, case-based learning, structured debates, collaborative projects) and the enhancement of formative and summative assessment practices, in line with empirical evidence demonstrating the positive impact of active learning on student performance and success. Third, the effectiveness of these uses depends on key conditions: the development of AI literacy and prompt engineering skills among educators and students; the redesign of assessment systems to ensure robustness against automation; and the establishment of ethical and institutional governance grounded in recognized risk management frameworks and international guidelines for AI in education.]]>
</description>
<dc:creator>
Mulwani  Makelele Basile, Sukadi  Mangwa Christelle, Nzuzi  Mavungu Gaël
</dc:creator>
<dc:date>2026-03-15</dc:date>
<dc:publisher>Science and Education Publishing</dc:publisher>
<prism:publicationDate>2026-03-15</prism:publicationDate>
<prism:number>3</prism:number>
<prism:volume>14</prism:volume>
<prism:startingPage>107</prism:startingPage>
<prism:endingPage>113</prism:endingPage>
<prism:doi>10.12691/education-14-3-5</prism:doi>
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