Primjena metoda podatkovne znanosti u analizi ljudskog kognitivnog opterećenja i višezadaćnih performansi

master's thesis

• Title (english): Application of data science methods in the analysis of human cognitive load and multitasking performance
• Author: Vid Juraj Ivković
• Mentor: Siniša Popović (mentor)
• Mentor: Krešimir Ćosić (komentor)
• Committee member: Milan Vrdoljak (predsjednik povjerenstva)
• Committee member: Siniša Popović (član povjerenstva)
• Committee member: Zvonko Trzun (član povjerenstva)
• Granter: University of Zagreb; (Croatian Defence Academy "Dr. Franjo Tuđman"); Zagreb
• Defense date and country: 2024-07-09, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Security and Defense Science
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Aviation, Rocket and Space Technology

Abstract

Ovaj istraživački rad istražuje višezadaćne sposobnosti korištenjem programa OpenMATB (Multi-Attribute Task Battery). Fokusiramo se na analizu performansi sudionika na tri od četiri osnovna zadatka OpenMATB-a, koji se odnose na nadgledanje sustava (engl. system monitoring), praćenje (engl. tracking), i upravljanje resursima (engl. resource management). Cilj je prikupiti podatke o performansama sudionika i njihovoj subjektivnoj procjeni kognitivnog opterećenja tijekom istodobnog izvođenja ovih zadataka. Koristeći statističke metode i tehnike strojnog učenja, analizirat ćemo ove podatke u cilju predviđanja performansi i raspoznavanja kognitivnog opterećenja sudionika na temelju informacija o trenutačnom stanju izvođenja svakog od navedenih zadataka. Naši rezultati pružaju uvid u ljudske višezadaćne sposobnosti i mogu imati primjene u područjima kao što su obuka pilota.

Abstract (english)

This research investigates multitasking abilities using the OpenMATB (Multi-Attribute Task Battery) program. We focus on analyzing participants' performance in three of the four fundamental OpenMATB tasks, which are related to: system monitoring, tracking and resource management. The aim is to collect data on participants' performance and their subjective assessment of cognitive load during the execution of these multitasking activities. By employing statistical methods and machine learning techniques, we will analyze these data to predict participants' performance and recognize cognitive workload based on information regarding the current state of execution of each respective task.. Our findings provide insights into human multitasking abilities and may have applications in fields such as pilot training.

• Keywords: OpenMATB; kognitivno opterećenje; ISA metoda; performanse; višezadaćni rad; strojno učenje
• Keywords (english): OpenMATB; cognitive workload; ISA method; performance; multitasking; machine learning
• Language: croatian
• URN:NBN: urn:nbn:hr:249:024109
• Study programme: Title: Military Engineering; Study programme type: university; Study level: graduate
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2024-11-04 10:01:16