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Examining the Effectiveness of New Technology in High School

Examining the Effectiveness of New Technology in High School. Aurora Vizcaíno & Manuel Prieto Escuela Superior de Informática de Ciudad Real Universidad de Castilla-La Mancha (ES) http://oreto.inf-cr.uclm.es.

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Examining the Effectiveness of New Technology in High School

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  1. Examining the Effectiveness of New Technology in High School Aurora Vizcaíno & Manuel Prieto Escuela Superior de Informática de Ciudad Real Universidad de Castilla-La Mancha (ES) http://oreto.inf-cr.uclm.es

  2. Improving some uses of New Technologies in Programming Learningat Higher Education Aurora Vizcaíno & Manuel Prieto Escuela Superior de Informática de Ciudad Real Universidad de Castilla-La Mancha (ES) http://oreto.inf-cr.uclm.es

  3. Résumé • Probleme. Aprentisage et enseigement de l´informtique a l´universté. Formation des habilités en programation. • Abordage. Sistemes bases en la colaboration et le conisance. Incorporation du concept d´etudiant virtuel. • Une solution. HabiPro, un programme de collaboration et distribué, conçu pour former habilities de programation des étudiants au niveau d'université. • Résultats. Obtenus à partir d'une expérience effectuée en utilisant HabiPro. • Notre groupe ORETO • CINTEC Aveiro, Juillet 2001 TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  4. Summary • Problem. Learning and teaching computing at University level. Developing skills in Computer Programming. • Approach. Knowledge and cooperative based systems. Incorporating the concept of Virtual Student • One solution. HabiPro a collaborative and distributed program designed to help in developing skills in programming students at university level. • Results. Obtained from an experiment carried out using HabiPro • Our group ORETO • CINTEC Aveiro, July 2001 TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  5. The problem: Learning to Program • Programming is a difficult topic to learn and to teach. • To teach because there are many abstract concepts like recursion or data structures. Teachers have problems to to find clear examples. • To learn because programming is (generally in first courses) a procedural discipline • Declarative knowledge is assumed to be easy to obtain, and skills acquisition difficult to acquire. Anderson 1983 • Procedural disciplines must be learnt « by doing » • Collaboration forces the development of self-regulatory skills; to explain opinions, articulate reasoning and other advantages. TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  6. Programming as a Discipline • 1968 ACM First orientations (From Mathematics) • 1975 IEEE Electric and Electronic Engineering • Curriculum’78 ACM. Programming and Programming architecture • 1983 IEEE Program in Computer Science & Engineering. Accreditation Board for Engineering & Technology. • 1990. Software Engineering IEEE and CMU • 2000 Software Engineering Coordinating Committee ACM- IEEE: SWEBOK. SW-E a recognised profession with a Body of Knowledge (http://www.swebok.org) TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  7. The discipline of programming in our conditions • Concienciar al alumno de los cambios en su entorno • Darle una visión global de la Programación • Propiciar el aprendizaje de fundamentos transferibles • Dar preferencia al desarrollo de habilidades • Equilibrio cantidad - profundidad • Integrar áreas no propiamente informáticas • Máxima importancia al trabajo práctico • Estimular el trabajo en grupos. TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  8. Two main ideas applicable in Programming Learning • The construction of the concept is creative and not a mechanic and passive process. A concept emerges and is formed in a middle of a complex operation oriented to solve some problem. Lev. S. Vygotsky • Obviously, in order to promote the functioning of the intelligence, it must be motivated by an affective force. Jean Piaget TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  9. Erroneous behaviours in new students • They use mainly button-up solutions • They tend to abuse of control structures • They don´t evaluate the importance of correct definitions of data types before coding. • Some processes become particularly difficult to be adapted because of previously acquired skills from other formal disciplines. Example recursion. Introductory Programming course (Last year) Registered Examined Passed 339 131 82 TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  10. Approach • Learning by doing • Cooperation • Virtual student • Developing Skills TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  11. Previous solutions • Systems • Lisp Tutor (Anderson & Reiser) • LAURA (Adam & Laurent) • PROUST (Johnson) • Ceilidh (Benford) • COACH (Secker) • CAPRA (verdejo). • Mainly centred in: • Correcting student´s bugs • Helping them to develop correct programs • Focus in syntactic and semantic mistakes TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  12. Proposal: Habi Pro • Habi Pro (Habitos en Programación) is conceived as a SW Product designed to help in developing good habits in Computer Programming. • Habi Pro is: • Distributed • Collaborative • Adaptive • Habi Pro tries: • To train students to create and debug efficient programs by themselves • To help students to develop good Programming habits including stile

  13. HabiPro interface

  14. Experiment • Subjects • The subjects were forty-six students from the First course • in Programming. Their ages were between eighteen • and twenty, and they didn’t have any previous knowledge • in Programming. • Methodology and Procedure • The experiment was divided into two sessions with • twenty-three students in each session. • In both sessions students had to try to solve twenty • exercises in group. • The maximum time to resolve the exercises was an hour.

  15. Exercises done in the first session

  16. Exercises solved in the second session

  17. Experiment • Discussion • Observing the two tables presented and comparing the average number of exercises solved by the groups who used HabiPro (14,6 exercises) and the average calculated in the first session (12,4) we can deduce that using HabiPro students solved more exercises. • On the other hand we calculated the statistical Eta in order to study whether there was any relation between the two variables • (number of exercises done and user or non-use of the tool). • We obtained an Eta value equal to 0.30 for the variable • ‘number of exercises done’ and a value of 0.73 for the variable ‘use or non-use of the tool’.

  18. Experiment Observing the second table, we can see that the group with less exercises done was the group formed of four people (group G), so we asked ourselves the reason for this. We studied the conversations stored in HabiPro. The group G conversation showed many sentences such as: Why don’t you answer? or Why don’t you propose anything?, that proved that the collaboration in this group wasn’t sufficient .

  19. Experiment Some data indicates that groups formed of four or more students could have communication and collaboration problems when they are working with HabiPro. During the experiment we could see that when there were two students working with HabiPro the collaboration was really good. The groups formed of three students, in the majority of the cases, worked by collaborating, although in some groups students commented the teacher that there was a person who never collaborated. So we think now for the future, that the best number of students to collaborate using HabiPro is two. With more persons the collaboration begins to decrease.

  20. Conclusions TICE´2000 Troyes Examining the Effectiveness of New Technology in High School M.Prieto, A. Vizcaíno

  21. Comunidad Autónoma de Castilla-La Mancha Area: 79,000 Km 2 Population: 1,700,000 Hab Universidad de Castilla-La Mancha Founded: 1985 6 Campuses in 5 provinces 35,000 Students Escuela Universitaria de Informática 1-2-3 cycles 7Research Groups SW quality & metrics SW-HW Co-design Computer Aided Learning

  22. Main Interest: Knowledge based systems • Human and artificial learning • Knowledge extraction from mass data • Fuzzy Knowledge • Movement capture and analysis • Co-operative and Knowledge based learning systems • Staff • 8 Lecturers ( 3 Drs ), scholars and students • Laboratory • Laboratorio de Captura de Movimiento (Motion Capture)

  23. International Conference on New Technologies in Science Education Aveiro, Portugal July 4 - 6 2001 Deadline for Submission: 1 May 2001 Call for papers & details in http://www.mat.ua.pt/cintec Universidade de Aveiro (PT) Universidad de Castilla-La Mancha (ES) • Presentation of models, tools and applications • as instructional aids using New Technologies • (not only Computer related) in Science Learning.

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