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10 Years of E-assessment & Math
M. Antonia Huertas
Computer Science Department
UOC
04/04/13 e-math 2013, UNED, Madrid 1
Introduction: E-assessment today
• The term ‘e-assessment’ began to be used widely from
the late 1990s
• Ofqual (Office of the Qualifications and Examinations
Regulator UK) defines e-assessment (2009) as:
“the use of electronic systems for the development,
operation and delivery of accredited qualification assessment
or the collection of performance evidence, which contributes
to the awarding of a unit or an accredited qualification”
http://www.ofqual.gov.uk/64.aspx
• E-assessments are tests which learners take onscreen
or online using computer technology. They are mainly
formed by multiple choice questions (MCQ)
04/04/13 e-math 2013, UNED, Madrid 2
Types of e-assessment in formal
education
• Summative, ‘high stakes’ assessments – examinations
where the results matter to the candidate and the
institution, and hence are both carefully regulated and
of public interest.
• Formative (or assessments for learning) – those
embedded within learning activities, are designed for
learners and teachers to monitor and plan their work.
• Technologies employed in these two settings may be
similar, approaches to risk and innovation are very
different.
04/04/13 e-math 2013, UNED, Madrid 3
Today use and benefits
• Benefits:
– Immediate feedback
– Assessment validity
– Space and time flexibility
– More efficient administration
• Not all benefits apply to all e-assessment use
• Poorly designed or implemented e-
assessment may achieve no benefits at all
• Benefits are not ‘automatic’
04/04/13 e-math 2013, UNED, Madrid 4
E-Learning technologies today
• Education is influenced by a lot of emerging
technologies
• http://c4lpt.co.uk/top-100-tools-2012/
• http://www.edtechmagazine.com/k12/article/
2012/11/6-hot-trends-educational-
technology-infographic
04/04/13 e-math 2013, UNED, Madrid 5
Features in e- assessment formats
• Question types: Short answers, Essay, Multiple Choice Questions (MCQ),
Multiple Response Questions (MRQ, Fill in the Blanks (FIB), Matchin,
Crossword puzzles.
04/04/13 e-math 2013, UNED, Madrid 6
Beyond multiple-choice questions
Automated scoring & feedback
• Automated scoring
– Mathematics marking
 Moodle + Wiris use in UOC experimental “Introduction of Maths for
Engineering”
– Programming languages & formal notations
– Short free text answer
• Automated feedback
– Intelligent Tutoring Systems (ITSs)
– Example for mathematics:
 ‘Carnegie Learning’s Cognitive Tutor’ at secondary and HE in USA
 ‘eFit’ for mathematics at lower secondary schools in Germany
04/04/13 e-math 2013, UNED, Madrid 7
Beyond multiple-choice questions
Adaptive assessment
• The system chooses which questions to ask next, based
on the candidate’s responses to previous questions.
(+) Better measure of student’s capabilities in a given time
(- ) Difficulty to ensure that the adaptivity functions correctly
• Technical methods of implementation commonly used
include dynamic item selection from a pool of items
based on statistical methods
04/04/13 e-math 2013, UNED, Madrid 8
Beyond multiple-choice questions
Simulations and serious gaming
• Used when students interaction with the real thing
is impractical (danger, too time consuming, too
expensive)
• Simulation technology is quite varied.
– Generic simulation engines (such as Expert Systems),
tailored for educational purpose
– But also computationally relatively simple software,
relying rather on rich and varied media
• Serious gaming refers to games with an educational
purpose. Rigorous assessment is a key area of
development in serious gaming
04/04/13 e-math 2013, UNED, Madrid 9
E-assessement generations
• We are in the Computer-based Testing Era:
– To improve the efficiency of testing procedures.
– E-assessment is centred on testing
• Generation 1 (1994-2002):
– Computerised conventional testing
– Automated scoring
• Generation 2 (2002-2012):
– Computerised adaptive testing
– MCQ & Moodle kind of systems
– Automated feedbak
04/04/13 e-math 2013, UNED, Madrid 10
Current and future e-Assessment strategies
Source : IPTS on the basis of Bennett, 2010; Bunderson, et al., 1989; Martin, 2008).
04/04/13 e-math 2013, UNED, Madrid 11
E-assessement generations
(the future)
• We are going to the Embedded Assessment Era
– Embedding assessment within the learning process
– Based on ‘Learning Analytics’ (Data analysis + beheavoural
tracking)
– Intelligent tutoring systems
– Automated feedback
• Generation 3:
– Continuous measurement to monitoring student’s achievement
trajectory
• Generation 4:
– Personalised feedback and tutoring
– Intelligent monitoring by means of knowledge engeeniering
• Requires technological advances
04/04/13 e-math 2013, UNED, Madrid 12
A Generation 2-3 case study
• Logic is an introductory course offered under the
Computer Science Degree programme at UOC.
• Looking for an e-assessment system to implement
formative e-assessment
• Design and implementation of an e-assessment
system for both knowledge and skill
• Design and implementation of a methodology for a
pilot in a real course in UOC
04/04/13 e-math 2013, UNED, Madrid 13
Architecture of the system
04/04/13 e-math 2013, UNED, Madrid 14
Formalization of the pilot
04/04/13 e-math 2013, UNED, Madrid 15
Formalization of the pilot
04/04/13 e-math 2013, UNED, Madrid 16
Results
• Formative continuous assessment is more correlated with
summative final assessment in the pilot group than in the
control group
• Helping to implement formative e-assessment, when skill
and knowledge acquisition have to be assessed
• From the statistical study it is not possible to state that the
student skills were improved (the ones evaluated in the
final examination), but they are not worsened although in
the pilot group students had a higher workload
• Teachers have the realistic chance to switch the previous
assessment model for a complete formative assessment
• Needing improvements: technologically and
methodologically.
04/04/13 e-math 2013, UNED, Madrid 17
My 10 years of e-assessment & Math
2002
• Logic
• MCQ tests
(automated scoring)
• Common test for all
students
2006
• Algebra
• Automated scoring
(Wiris)
• Individual test (n
kinds of exercises
with parameters)
2009
• Logic
• ITS for Learning Logic
• Automated feedback
step by step
excercises
2012
• Logic
• E-assessment system
(Moodle + ITS)
• Automated scoring
and feedback for
knowledge and skills
04/04/13 e-math 2013, UNED, Madrid 18
Obrigada
Thank you
Gracias
04/04/13 e-math 2013, UNED, Madrid 19
04/04/13 e-math 2013, UNED, Madrid 20
04/04/13 e-math 2013, UNED, Madrid 21
04/04/13 e-math 2013, UNED, Madrid 22
04/04/13 e-math 2013, UNED, Madrid 23
04/04/13 e-math 2013, UNED, Madrid 24
04/04/13 e-math 2013, UNED, Madrid 25
04/04/13 e-math 2013, UNED, Madrid 26
04/04/13 e-math 2013, UNED, Madrid 27

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10 Years of E-assessment & Math

  • 1. 10 Years of E-assessment & Math M. Antonia Huertas Computer Science Department UOC 04/04/13 e-math 2013, UNED, Madrid 1
  • 2. Introduction: E-assessment today • The term ‘e-assessment’ began to be used widely from the late 1990s • Ofqual (Office of the Qualifications and Examinations Regulator UK) defines e-assessment (2009) as: “the use of electronic systems for the development, operation and delivery of accredited qualification assessment or the collection of performance evidence, which contributes to the awarding of a unit or an accredited qualification” http://www.ofqual.gov.uk/64.aspx • E-assessments are tests which learners take onscreen or online using computer technology. They are mainly formed by multiple choice questions (MCQ) 04/04/13 e-math 2013, UNED, Madrid 2
  • 3. Types of e-assessment in formal education • Summative, ‘high stakes’ assessments – examinations where the results matter to the candidate and the institution, and hence are both carefully regulated and of public interest. • Formative (or assessments for learning) – those embedded within learning activities, are designed for learners and teachers to monitor and plan their work. • Technologies employed in these two settings may be similar, approaches to risk and innovation are very different. 04/04/13 e-math 2013, UNED, Madrid 3
  • 4. Today use and benefits • Benefits: – Immediate feedback – Assessment validity – Space and time flexibility – More efficient administration • Not all benefits apply to all e-assessment use • Poorly designed or implemented e- assessment may achieve no benefits at all • Benefits are not ‘automatic’ 04/04/13 e-math 2013, UNED, Madrid 4
  • 5. E-Learning technologies today • Education is influenced by a lot of emerging technologies • http://c4lpt.co.uk/top-100-tools-2012/ • http://www.edtechmagazine.com/k12/article/ 2012/11/6-hot-trends-educational- technology-infographic 04/04/13 e-math 2013, UNED, Madrid 5
  • 6. Features in e- assessment formats • Question types: Short answers, Essay, Multiple Choice Questions (MCQ), Multiple Response Questions (MRQ, Fill in the Blanks (FIB), Matchin, Crossword puzzles. 04/04/13 e-math 2013, UNED, Madrid 6
  • 7. Beyond multiple-choice questions Automated scoring & feedback • Automated scoring – Mathematics marking  Moodle + Wiris use in UOC experimental “Introduction of Maths for Engineering” – Programming languages & formal notations – Short free text answer • Automated feedback – Intelligent Tutoring Systems (ITSs) – Example for mathematics:  ‘Carnegie Learning’s Cognitive Tutor’ at secondary and HE in USA  ‘eFit’ for mathematics at lower secondary schools in Germany 04/04/13 e-math 2013, UNED, Madrid 7
  • 8. Beyond multiple-choice questions Adaptive assessment • The system chooses which questions to ask next, based on the candidate’s responses to previous questions. (+) Better measure of student’s capabilities in a given time (- ) Difficulty to ensure that the adaptivity functions correctly • Technical methods of implementation commonly used include dynamic item selection from a pool of items based on statistical methods 04/04/13 e-math 2013, UNED, Madrid 8
  • 9. Beyond multiple-choice questions Simulations and serious gaming • Used when students interaction with the real thing is impractical (danger, too time consuming, too expensive) • Simulation technology is quite varied. – Generic simulation engines (such as Expert Systems), tailored for educational purpose – But also computationally relatively simple software, relying rather on rich and varied media • Serious gaming refers to games with an educational purpose. Rigorous assessment is a key area of development in serious gaming 04/04/13 e-math 2013, UNED, Madrid 9
  • 10. E-assessement generations • We are in the Computer-based Testing Era: – To improve the efficiency of testing procedures. – E-assessment is centred on testing • Generation 1 (1994-2002): – Computerised conventional testing – Automated scoring • Generation 2 (2002-2012): – Computerised adaptive testing – MCQ & Moodle kind of systems – Automated feedbak 04/04/13 e-math 2013, UNED, Madrid 10
  • 11. Current and future e-Assessment strategies Source : IPTS on the basis of Bennett, 2010; Bunderson, et al., 1989; Martin, 2008). 04/04/13 e-math 2013, UNED, Madrid 11
  • 12. E-assessement generations (the future) • We are going to the Embedded Assessment Era – Embedding assessment within the learning process – Based on ‘Learning Analytics’ (Data analysis + beheavoural tracking) – Intelligent tutoring systems – Automated feedback • Generation 3: – Continuous measurement to monitoring student’s achievement trajectory • Generation 4: – Personalised feedback and tutoring – Intelligent monitoring by means of knowledge engeeniering • Requires technological advances 04/04/13 e-math 2013, UNED, Madrid 12
  • 13. A Generation 2-3 case study • Logic is an introductory course offered under the Computer Science Degree programme at UOC. • Looking for an e-assessment system to implement formative e-assessment • Design and implementation of an e-assessment system for both knowledge and skill • Design and implementation of a methodology for a pilot in a real course in UOC 04/04/13 e-math 2013, UNED, Madrid 13
  • 14. Architecture of the system 04/04/13 e-math 2013, UNED, Madrid 14
  • 15. Formalization of the pilot 04/04/13 e-math 2013, UNED, Madrid 15
  • 16. Formalization of the pilot 04/04/13 e-math 2013, UNED, Madrid 16
  • 17. Results • Formative continuous assessment is more correlated with summative final assessment in the pilot group than in the control group • Helping to implement formative e-assessment, when skill and knowledge acquisition have to be assessed • From the statistical study it is not possible to state that the student skills were improved (the ones evaluated in the final examination), but they are not worsened although in the pilot group students had a higher workload • Teachers have the realistic chance to switch the previous assessment model for a complete formative assessment • Needing improvements: technologically and methodologically. 04/04/13 e-math 2013, UNED, Madrid 17
  • 18. My 10 years of e-assessment & Math 2002 • Logic • MCQ tests (automated scoring) • Common test for all students 2006 • Algebra • Automated scoring (Wiris) • Individual test (n kinds of exercises with parameters) 2009 • Logic • ITS for Learning Logic • Automated feedback step by step excercises 2012 • Logic • E-assessment system (Moodle + ITS) • Automated scoring and feedback for knowledge and skills 04/04/13 e-math 2013, UNED, Madrid 18
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Editor's Notes

  1. CQ)
  2. NOTE: (1) not all these benefits apply to all e-assessment use & (2) poorly designed or implemented e-assessment may achieve no benefits at all – the gains are not ‘automatic’.
  3. TOP 100: 11-Moodel (VER DOCUMENTO RESUMEN) EDTECH: Currently use of on-line assessment 75%
  4. Blackboard is commercial Hot Potatoes and OpenMark are application specific MoodleXML, a common format supported by one of the popular and most used open source LMS, Moodle and IMS QTI which is a defector standard
  5. Embedded Assessment, which is based on the notion of ‘Learning Analytics’, i.e. the interpretation of data about students’ proficiency in order to assess academic progress, predict future performance, and tailor education to individual students
  6. Embedded Assessment, which is based on the notion of ‘Learning Analytics’, i.e. the interpretation of data about students’ proficiency in order to assess academic progress, predict future performance, and tailor education to individual students