A Graduate Level Personalized Learning Environment in the Field of f-NIRS Signal Processing

Active student involvement and instruction through experience in everyday contexts are pedagogical approaches suitable to promote inquiry-based learning and improve learners’ cognitive skills. Nevertheless, many university and postgraduate courses offer lecture-based instructions of theoretical concepts to the students; little attention is still devoted to design hands-on activities, to improve practical/technical competencies and enhance students’ effective understanding of the concepts. The development of a personalized, student-centered learning environment that encourages teamwork and inquiry-based learning aligns with the contemporary push for interdisciplinary education in bioengineering fields. This is particularly relevant for fostering expertise in emerging technologies like functional Near-Infrared Spectroscopy (f-NIRS). In this framework, this paper reports a lab activity for bioelectronic engineering and/or biomedical science students focused on analyzing prefrontal cortex activation during a memory task, processing the f-NIRS signals. This pilot activity, conducted at the University of Palermo (Italy), involved Master’s and Ph.D. students working in teams to address challenges in experimental design. The study combines cutting-edge biosignal detection techniques with innovative educational strategies, offering substantial contributions to both bioengineering and educational research. The outcomes suggest that a hands-on and student-centered laboratory, experienced through a methodical sequence of self-directed learning activities, could considerably boost the student motivation to learn and the level of engagement in bioengineering and biosciences.

Authors

Institutions

Publication Details

Journal
Information
Published
2025-02-21
DOI
https://doi.org/10.3390/info16030162
Primary Topic
Sensor Technology and Measurement Systems
Type
article
Field-Weighted Citation Impact
0.00

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

A Graduate Level Personalized Learning Environment in the Field of f-NIRS Signal Processing

Giuseppe Costantino Giaconia, Dominique Persano Adorno
1 links
Information
Sensor Technology and Measurement Systems
article

A Graduate Level Personalized Learning Environment in the Field of f-NIRS Signal Processing

Giuseppe Costantino Giaconia, Dominique Persano Adorno
article en

Abstract

Active student involvement and instruction through experience in everyday contexts are pedagogical approaches suitable to promote inquiry-based learning and improve learners’ cognitive skills. Nevertheless, many university and postgraduate courses offer lecture-based instructions of theoretical concepts to the students; little attention is still devoted to design hands-on activities, to improve practical/technical competencies and enhance students’ effective understanding of the concepts. The development of a personalized, student-centered learning environment that encourages teamwork and inquiry-based learning aligns with the contemporary push for interdisciplinary education in bioengineering fields. This is particularly relevant for fostering expertise in emerging technologies like functional Near-Infrared Spectroscopy (f-NIRS). In this framework, this paper reports a lab activity for bioelectronic engineering and/or biomedical science students focused on analyzing prefrontal cortex activation during a memory task, processing the f-NIRS signals. This pilot activity, conducted at the University of Palermo (Italy), involved Master’s and Ph.D. students working in teams to address challenges in experimental design. The study combines cutting-edge biosignal detection techniques with innovative educational strategies, offering substantial contributions to both bioengineering and educational research. The outcomes suggest that a hands-on and student-centered laboratory, experienced through a methodical sequence of self-directed learning activities, could considerably boost the student motivation to learn and the level of engagement in bioengineering and biosciences.

InformationVol. 16(3)
University of Palermo (IT)
European Commission
Openalex Percentile: Top 97%
Sensor Technology and Measurement Systems
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

A Graduate Level Personalized Learning Environment in the Field of f-NIRS Signal Processing — Giuseppe Costantino Giaconia, Dominique Persano Adorno · Information (2025) | TGRS Research Map | TGRS