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PID2020-117523GB-I00

Financiado

COLLECTING AND PROCESSING EVIDENCE THAT MATTERS IN EDUCATION: PENTABILITIES AND...

COLLECTING AND PROCESSING EVIDENCE THAT MATTERS IN EDUCATION: PENTABILITIES AND ML-ASSISTED HUMAN DECISION MAKING KEY TO PROGRESS IS HAVING A WELL-DEFINED GOAL THAT CAN BE UNDERSTOOD, SHARED, AND FOR WHICH PROGRESS IS OBSERVABLE, THE GOAL OF EDUCATION IS TO FACILITATE THAT INDIVIDUALS CONTRIBUTE AND SUCCEED IN THEIR WORKPLACE, FAMILY ENVIRON... ver más

01/01/2020

FUNDACIO INSTITUTE...

23K€

Presupuesto del proyecto: 23K€

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FUNDACIO INSTITUTE OF POLITICAL ECONOMY AND G... Investigación y desarrollo experimental en ciencias naturales y técnicas asociacion

TRL 3-4 | 50K€

Financiación concedida El organismo AGENCIA ESTATAL DE INVESTIGACIÓN notifico la concesión del proyecto el día 2020-01-01 No tenemos la información de la convocatoria

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FUNDACIO INSTITUTE OF POLITI...

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Líder del proyecto

FUNDACIO INSTITUTE OF POLITICAL ECONOMY AND G... Investigación y desarrollo experimental en ciencias naturales y técnicas asociacion

TRL 3-4 | 50K€

Presupuesto del proyecto 23K€

Descripción del proyecto KEY TO PROGRESS IS HAVING A WELL-DEFINED GOAL THAT CAN BE UNDERSTOOD, SHARED, AND FOR WHICH PROGRESS IS OBSERVABLE, THE GOAL OF EDUCATION IS TO FACILITATE THAT INDIVIDUALS CONTRIBUTE AND SUCCEED IN THEIR WORKPLACE, FAMILY ENVIRONMENTS AND SOCIAL GROUPS, TEST SCORES HAVE EXHAUSTED THEIR VALUE TO MEASURE PROGRESS IN ACHIEVING THIS GOAL, SOCIAL AND PERSONAL SKILLS HAVE PROVEN TO BE KEY TO FUTURE SUCCESS BUT HAVE NOT BEEN CENTRAL IN EDUCATION YET BECAUSE OF LACK OF EVIDENCE-BASED MEASURES, WHICH HAS GREATLY INHIBITED THE POWER OF EDUCATION TO TRANSFORM SOCIETIES, THE PROJECT PROVIDES THE FIRST METHODOLOGY TO COLLECT 34 BEHAVIORS, THAT WE CALL PENTABILITIES, THAT PROVIDE EVIDENCE OF COGNITIVE AND NON-COGNITIVE SKILLS OF INDIVIDUALS, THE AIMS IS TO PROVE ITS POWER FOR THREE MAIN PURPOSES: 1) TO FACILITATE FORMATIVE ASSESSMENT AND HENCE TO IMPROVE GROWTH OF STUDENTS AND PRACTITIONERS, 2) TO IDENTIFY BETTER PRACTICES AND 3) TO IMPROVE THE MATCH QUALITY OF INDIVIDUALS TO PROGRAMS OR JOBS, ON THE OTHER HAND, ONCE THE RELEVANT DATA IS AVAILABLE, HOW CAN WE MAKE BEST USE OF IT TO FACILITATE OPTIMAL INDIVIDUAL AND SOCIETAL DECISION MAKING? MACHINE LEARNING IS NOW BEING USED TO ASSIST POLICY, BUT IT RAISES TWO IMPORTANT CONCERNS, THE FIRST IS THAT ML CAN HAVE A LARGE IMPACT ON THE FAIRNESS OF THE SYSTEM, WE EXPLORE DESIGN FEATURES OF ML ALGORITHMS THAT CAN IMPROVE FAIRNESS IN CENTRALIZED PLATFORMS BY CHANGING HOW CHOICES ARE MADE WITHIN THE PLATFORM AND OPTIMALLY DEFINING WHO SHOULD DECIDE WHAT, SECOND, IN MANY INSTANCES ML TELLS YOU WHAT TO DO, BUT NOT WHY, WHICH DOES NOT FACILITATE ML HELPING INDIVIDUALS UNDERSTAND THE DATA TO ENHANCE THEIR DECISION MAKING, WE AIM AT DESIGNING ML ALGORITHMS THAT ARE DESIGNED TO OPTIMIZE HOW INFORMATION IN THE DATA IS VISUALIZED TO FACILITATE OPTIMAL HUMAN DECISION MAKING, THIS INVOLVES INCLUDING THE HUMAN REACTION TO ML INTO THE TRAINING DATA, A NOVEL APPROACH THAT THIS PROJECT PUSHES FORWARD TO MAKE THE BEST USE OF ML IN POLICY, 21ST CENTURY SKILLS\PENTABILITIES\ALGORITHM DESIGN

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