@article {857,
	title = {ADOPTION OF DIGITAL STORYTELLING TOOL IN NATURAL SCIENCES AND TECHNOLOGY EDUCATION BY PRE-SERVICE TEACHERS USING THE TECHNOLOGY ACCEPTANCE MODEL},
	journal = {Journal of Baltic Science Education},
	volume = {19},
	year = {2020},
	month = {June/2020},
	pages = {Continuous},
	type = {Original article},
	chapter = {429-453},
	abstract = {This research aimed to contribute to the overall understanding of pre-service teachers{\textquoteright} acceptance of the Digital Storytelling (DS) tool. The primary associations of the Technology Acceptance Model (TAM) were tested in the academic years 2017/2018 and 2018/2019 for statistical significance when the effects of the pre-service training teachers{\textquoteright} digital age and status were controlled. Data from 296 pre-service teachers, from second and third study year, majority women considered vulnerable group were collected. The factor analysis and invariance tests on basic TAM were performed. The results revealed that DS tool usage intention was a function of perceived usefulness and ease of use. This research established the TAM applicability with the control variables addition to model the DS tool acceptance by pre-service teachers, as didactic material for natural sciences and technology education. Configural, metric, and scalar invariance were confirmed across both cross-temporal and cross-sectorial groups. Perceived ease of use of DS has strongly influenced both usefulness (β=.571, t=11.958, p<.0001) and intention to use of DS (β=.763, t=19.914, p<.0001), under the influences of the control variables. The outcomes contributed to the general understanding of DS pre-service teachers{\textquoteright} adoption relevant for natural sciences and technology education and for recognition of vulnerable category behavior.},
	keywords = {digital storytelling tool, natural sciences didactics, pre-service teachers{\textquoteright} digital age, pre-service teachers{\textquoteright} status, TAM model, technology education didactics},
	issn = {1648-3898},
	doi = {https://doi.org/10.33225/jbse/20.19.429},
	url = {http://oaji.net/articles/2020/987-1591087866.pdf},
	author = {Iuliana Lazar and Georgeta Panisoara and Ion-Ovidiu Panisoara}
}
@article {983,
	title = {THE EFFECTS OF ONLINE TEACHING ON STUDENTS{\textquoteright} ACADEMIC PROGRESS IN STEM},
	journal = {Journal of Baltic Science Education},
	volume = {19},
	year = {2020},
	month = {December/2020},
	pages = {Continuous},
	type = {Original article},
	chapter = {1106-1124},
	abstract = {Online teaching environment is a challenge for science, technology, engineering, and mathematics (STEM) in-service teachers who feel worried about their ability to succeed in what might be an unfamiliar learning environment. This research focused on testing the effects of perceived risks and concerns by in-service teachers during online-only classes due to the coronavirus outbreak on student academic progress requirements across the different STEM disciplines. The research hypotheses were tested on a sample of 1444 in-service teachers teaching exclusively in the online environment, in Romania. A structural equation model was used to explore the possible links among two external variables (pedagogical and technological perceived risks), one mediator variable (student engagement), one control variable (school settings), and one output variable (student academic progress requirements). The results revealed significant negative paths from challenges mediated by student engagement to student academic progress, as well as positive paths from them to mediator factor. The school setting categories were negatively correlated with both perceived risk dimensions. The moderator role of student engagement on the challenges-outcome link was supported. The online teaching effects on student{\textquoteright}s academic progress varied across the different STEM disciplines. The relevant common features for all STEM disciplines were further then demonstrated.  },
	keywords = {in-service teachers, online class, pandemic emergency, STEM, structural equation modelling, student academic progress},
	issn = {1648-3898},
	doi = {https://doi.org/10.33225/jbse/20.19.1106},
	url = {http://oaji.net/articles/2021/987-1613414653.pdf},
	author = {Ion-Ovidiu Panisoara and Ruxandra Chirca and Iuliana Lazar}
}
