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First Principles of CS Instruction A perspective on CS Education K. Becker
Overview Instructional Design & Computer Science Education M. David Merrill Merrill’s First Principles of Instruction
Instructional Design &  Computer Science Education Learning and ID theories have had relatively little impact on how computer science is taught.  A great many courses are still taught much the same way they were a generation ago .
Here’s what happens if we search for information on “Instructional Design” &  “Computer Science Education”….
 
 
 
 
Instructional Design &  Computer Science Education Technology is used less as a system or tool for the support of learning and more as an apparatus on which to run programs and develop documentation .
M. David Merrill Component Display Theory Elaboration Theory (developed in collaboration with Charles M. Reigeluth) Instructional Transaction Theory the TICCIT CAI System First Principles of Instruction (2002) PhD ’64 (Ed. Psych.) Brigham Young / Utah State
“ If you don't provide adequate practice,  if you don't have an adequate knowledge structure,  if you don't provide adequate guidance,  people don't learn. “
Appropriate practice is the single most neglected aspect of effective instruction.
Information is Not Instruction  Many current instructional models suggest that the most effective learning products or environments are those that are problem centered and involve the student in a cycle of learning that involves four distinct phases: activation of prior experience demonstration of skills application of skills integration of these skills into real-world activities
Merrill’s First Principles of Instruction   The success of a given instructional program will be directly proportional to how well and how deliberately the first principles are implemented.
Merrill’s First Principles of Instruction   Problem  “ Learning is facilitated when learners are engaged in solving real-world problems.”  Activation   “ Learning is facilitated when existing knowledge is activated as a foundation for new knowledge.”   Demonstration  “ Learning is facilitated when new knowledge is demonstrated to the learner.”  Application   “ Learning is facilitated when new knowledge is applied by the learner.”  Integration   “ Learning is facilitated when new knowledge is integrated into the learner’s world.”
Problem  engagement in solving real-world problems PBL is more deliberate than what we do. structured,  guided  approach delineation of the problem and its domain research and discovery of relevant knowledge and data presentation of a solution and a reflection on what was learned deliberate and conscious connection with existing knowledge.  Accounting examples? Management? Employee Records?   look seriously at how students spend their time Games, internet communication, music, … Offer choices (more for seniors / less for freshmen)  For example, the classic arcade game  Frogger , a hospital emergency room simulation, and a dynamic restaurant menu system are all problems that lend themselves to the use of inheritance and polymorphism.  If the pedagogical objectives are clearly defined, then the subject matter can become flexible, thereby creating relevance, and the potential for a personal connection with the problem.
PBL Steps Topic Introduction Explore the issues. What do we already know? What do we want to know? Develop, and write out, the problem statement in your own words.   Hypothesize: List out possible solutions. List actions to be taken with a timeline. Additional Information What do we need to know? Closure Write up your solution with its supporting documentation, and submit it. Review your performance. Data Requests Learning Issues
Problem  engagement in solving real-world problems Is the courseware presented in the context of real-world problems?  Are learners shown the problem, engaged at the task as well as the operation level, and involved in a progression of problems?
Activation   activate existing knowledge as foundation for new knowledge  To activate existing knowledge, we must know what that existing knowledge is.  cell phones, email, surf the web, find music and videos, and play games.  proficient, yet lack sophistication in searching and the critical assessment of resources. acknowledge their skills, without either assuming too high a level of sophistication, nor too much nescience. One will discourage students, while the other will bore them. Either way, they will become disengaged and motivation will suffer.  Example: Greedy algorithms by making change.  Searching for a name in a phonebook as a means of introducing a binary search.  : relevance changes over time.  If we wish to start from where the students are, then we must be prepared to assess the knowledge they bring to the situation regularly.
Activation   activate existing knowledge as foundation for new knowledge  Does the courseware attempt to activate relevant prior knowledge or experience?  Are learners directed to recall relevant past experience or provided relevant experience?  Are they encouraged to use some organizing structure?
Demonstration  Learning objects can be useful here Live, in class demonstrations of programs are more effective than simply reading through and explaining code Modeling behavior  such as answering a question by performing a search on the internet, (including rapid assessment of potential resources)  Develop a solution to a problem on the fly – including errors and blind alleys.  Maybe the 100 th  time for us, but the first time for them We learn a great deal from our mistakes and to some extent the mistakes of others.  Allow our students to observe error recovery.
Demonstration  Does the courseware demonstrate what is to be learned rather than merely telling information about what is to be learned?  Are the demonstrations consistent with the instructional goals?  Is learner guidance employed?  Do media enhance learning?
Application   by the learner The CS cup runneth over with content.  The body of knowledge associated with the discipline has grown and evolved over the last 40 years and in our desire to provide students with as much information and knowledge as we can, we sometimes forget that they still need time to absorb the information - and this includes time for practice.  Chess masters, musicians, swimmers, and others have been shown to require on average ten years to achieve expert status!  What makes us think we can create expert programmers and computer scientists in just four?
Application   by the learner We can no longer cover the same ground in an undergraduate program as we did when we were students, yet we cling to a desire to do so, and to add all that we have learned since graduating as well.  Modern theories of education, including Merrill’s imply that students will be better prepared through the acquisition of deep knowledge in fewer areas than through a shallow or cursory acquaintance with many.  We do our students a disservice by attempting to move on to the next topic too quickly.  One the other hand some topics can be taught using a spiral approach. The topic can be introduced but treated superficially in one course, and then addressed in greater depth in one or more subsequent courses.  Recursion, algorithm analysis, and program testing  Others, like ethics, professional practice, and communication skills can also be broken up and spread across multiple courses, but lend themselves more to sectioned, in-depth study than to layering from superficial overviews to deep learning.  A Mile Wide and an Inch Deep
Application   by the learner Do learners have an opportunity to apply their newly acquired knowledge or skill?  Is the application consistent with the instructional goals, and does it involve a varied sequence of problems with feedback?  Are learners provided with gradually diminished coaching?
Integration   new knowledge is integrated into the learner’s world It is like coming full circle – we start from where the student is, and end by helping them convert new knowledge into a new starting point.  If the curriculum is well integrated, subsequent courses can quite literally pick up where the others left off.  If it is not, time will be required in each course to re-assess what knowledge the students bring. Typical : 5-10 distinct assignments. There is no time in between to reflect, and in an effort to maintain interest, each problem bears little relationship to the last.  This kind of approach does not promote integration of learning.  While it is sometimes impractical to create assignments that logically follow one another, attempts should be made to do so.  When this is not possible, both practical and conceptual connections can be made explicit. At the course level, content can and should be tied to the students’ lives, current events, research, and professional practice whenever possible.  For example, reading an article like Walpole’s “ Designing Games for the Wage Slave ” connects well with student’s lives, can be used to discuss software design on many levels,  and  can be used as the basis for assessment criteria on a programming assignment.
Integration   new knowledge is integrated into the learner’s world Does the courseware provide techniques that encourage learners to integrate (transfer) the new knowledge or skill into their everyday life? Do learners have an opportunity to publicly demonstrate their new knowledge, reflect on their new knowledge, and create new ways to use their new knowledge?
Conclusions Courses can benefit from a more deliberate approach to the design of instruction . Freshmen have a broader base of experience than they used to, and integrating this experience into our courses forms connections that engages students . Contextualizing their experience draws them in, and maintaining relevance while guiding their practice will sustain them .
Learning  About vs. Learning  To Be Merrill, M. D. (2001). First Principles of Instruction.  Journal of Structural Learning & Intelligent Systems, 14 (4), 459-466. http://id2.usu.edu/Papers/5FirstPrinciples.PDF#search=%22First%20Principles%20of%20Instruction%22   Merrill, M. D. (2002). A Pebble-in-the-Pond Model for Instructional Design.  Performance Improvement, 41 (7), 39-44. http://cito.byuh.edu/merrill/text/papers/pebbleinthepond.pdf

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First Principles Of Cs Instruction

  • 1. First Principles of CS Instruction A perspective on CS Education K. Becker
  • 2. Overview Instructional Design & Computer Science Education M. David Merrill Merrill’s First Principles of Instruction
  • 3. Instructional Design & Computer Science Education Learning and ID theories have had relatively little impact on how computer science is taught. A great many courses are still taught much the same way they were a generation ago .
  • 4. Here’s what happens if we search for information on “Instructional Design” & “Computer Science Education”….
  • 5.  
  • 6.  
  • 7.  
  • 8.  
  • 9. Instructional Design & Computer Science Education Technology is used less as a system or tool for the support of learning and more as an apparatus on which to run programs and develop documentation .
  • 10. M. David Merrill Component Display Theory Elaboration Theory (developed in collaboration with Charles M. Reigeluth) Instructional Transaction Theory the TICCIT CAI System First Principles of Instruction (2002) PhD ’64 (Ed. Psych.) Brigham Young / Utah State
  • 11. “ If you don't provide adequate practice, if you don't have an adequate knowledge structure, if you don't provide adequate guidance, people don't learn. “
  • 12. Appropriate practice is the single most neglected aspect of effective instruction.
  • 13. Information is Not Instruction Many current instructional models suggest that the most effective learning products or environments are those that are problem centered and involve the student in a cycle of learning that involves four distinct phases: activation of prior experience demonstration of skills application of skills integration of these skills into real-world activities
  • 14. Merrill’s First Principles of Instruction The success of a given instructional program will be directly proportional to how well and how deliberately the first principles are implemented.
  • 15. Merrill’s First Principles of Instruction Problem “ Learning is facilitated when learners are engaged in solving real-world problems.” Activation “ Learning is facilitated when existing knowledge is activated as a foundation for new knowledge.” Demonstration “ Learning is facilitated when new knowledge is demonstrated to the learner.” Application “ Learning is facilitated when new knowledge is applied by the learner.” Integration “ Learning is facilitated when new knowledge is integrated into the learner’s world.”
  • 16. Problem engagement in solving real-world problems PBL is more deliberate than what we do. structured, guided approach delineation of the problem and its domain research and discovery of relevant knowledge and data presentation of a solution and a reflection on what was learned deliberate and conscious connection with existing knowledge. Accounting examples? Management? Employee Records? look seriously at how students spend their time Games, internet communication, music, … Offer choices (more for seniors / less for freshmen) For example, the classic arcade game Frogger , a hospital emergency room simulation, and a dynamic restaurant menu system are all problems that lend themselves to the use of inheritance and polymorphism. If the pedagogical objectives are clearly defined, then the subject matter can become flexible, thereby creating relevance, and the potential for a personal connection with the problem.
  • 17. PBL Steps Topic Introduction Explore the issues. What do we already know? What do we want to know? Develop, and write out, the problem statement in your own words. Hypothesize: List out possible solutions. List actions to be taken with a timeline. Additional Information What do we need to know? Closure Write up your solution with its supporting documentation, and submit it. Review your performance. Data Requests Learning Issues
  • 18. Problem engagement in solving real-world problems Is the courseware presented in the context of real-world problems? Are learners shown the problem, engaged at the task as well as the operation level, and involved in a progression of problems?
  • 19. Activation activate existing knowledge as foundation for new knowledge To activate existing knowledge, we must know what that existing knowledge is. cell phones, email, surf the web, find music and videos, and play games. proficient, yet lack sophistication in searching and the critical assessment of resources. acknowledge their skills, without either assuming too high a level of sophistication, nor too much nescience. One will discourage students, while the other will bore them. Either way, they will become disengaged and motivation will suffer. Example: Greedy algorithms by making change. Searching for a name in a phonebook as a means of introducing a binary search. : relevance changes over time. If we wish to start from where the students are, then we must be prepared to assess the knowledge they bring to the situation regularly.
  • 20. Activation activate existing knowledge as foundation for new knowledge Does the courseware attempt to activate relevant prior knowledge or experience? Are learners directed to recall relevant past experience or provided relevant experience? Are they encouraged to use some organizing structure?
  • 21. Demonstration Learning objects can be useful here Live, in class demonstrations of programs are more effective than simply reading through and explaining code Modeling behavior such as answering a question by performing a search on the internet, (including rapid assessment of potential resources) Develop a solution to a problem on the fly – including errors and blind alleys. Maybe the 100 th time for us, but the first time for them We learn a great deal from our mistakes and to some extent the mistakes of others. Allow our students to observe error recovery.
  • 22. Demonstration Does the courseware demonstrate what is to be learned rather than merely telling information about what is to be learned? Are the demonstrations consistent with the instructional goals? Is learner guidance employed? Do media enhance learning?
  • 23. Application by the learner The CS cup runneth over with content. The body of knowledge associated with the discipline has grown and evolved over the last 40 years and in our desire to provide students with as much information and knowledge as we can, we sometimes forget that they still need time to absorb the information - and this includes time for practice. Chess masters, musicians, swimmers, and others have been shown to require on average ten years to achieve expert status! What makes us think we can create expert programmers and computer scientists in just four?
  • 24. Application by the learner We can no longer cover the same ground in an undergraduate program as we did when we were students, yet we cling to a desire to do so, and to add all that we have learned since graduating as well. Modern theories of education, including Merrill’s imply that students will be better prepared through the acquisition of deep knowledge in fewer areas than through a shallow or cursory acquaintance with many. We do our students a disservice by attempting to move on to the next topic too quickly. One the other hand some topics can be taught using a spiral approach. The topic can be introduced but treated superficially in one course, and then addressed in greater depth in one or more subsequent courses. Recursion, algorithm analysis, and program testing Others, like ethics, professional practice, and communication skills can also be broken up and spread across multiple courses, but lend themselves more to sectioned, in-depth study than to layering from superficial overviews to deep learning. A Mile Wide and an Inch Deep
  • 25. Application by the learner Do learners have an opportunity to apply their newly acquired knowledge or skill? Is the application consistent with the instructional goals, and does it involve a varied sequence of problems with feedback? Are learners provided with gradually diminished coaching?
  • 26. Integration new knowledge is integrated into the learner’s world It is like coming full circle – we start from where the student is, and end by helping them convert new knowledge into a new starting point. If the curriculum is well integrated, subsequent courses can quite literally pick up where the others left off. If it is not, time will be required in each course to re-assess what knowledge the students bring. Typical : 5-10 distinct assignments. There is no time in between to reflect, and in an effort to maintain interest, each problem bears little relationship to the last. This kind of approach does not promote integration of learning. While it is sometimes impractical to create assignments that logically follow one another, attempts should be made to do so. When this is not possible, both practical and conceptual connections can be made explicit. At the course level, content can and should be tied to the students’ lives, current events, research, and professional practice whenever possible. For example, reading an article like Walpole’s “ Designing Games for the Wage Slave ” connects well with student’s lives, can be used to discuss software design on many levels, and can be used as the basis for assessment criteria on a programming assignment.
  • 27. Integration new knowledge is integrated into the learner’s world Does the courseware provide techniques that encourage learners to integrate (transfer) the new knowledge or skill into their everyday life? Do learners have an opportunity to publicly demonstrate their new knowledge, reflect on their new knowledge, and create new ways to use their new knowledge?
  • 28. Conclusions Courses can benefit from a more deliberate approach to the design of instruction . Freshmen have a broader base of experience than they used to, and integrating this experience into our courses forms connections that engages students . Contextualizing their experience draws them in, and maintaining relevance while guiding their practice will sustain them .
  • 29. Learning About vs. Learning To Be Merrill, M. D. (2001). First Principles of Instruction. Journal of Structural Learning & Intelligent Systems, 14 (4), 459-466. http://id2.usu.edu/Papers/5FirstPrinciples.PDF#search=%22First%20Principles%20of%20Instruction%22 Merrill, M. D. (2002). A Pebble-in-the-Pond Model for Instructional Design. Performance Improvement, 41 (7), 39-44. http://cito.byuh.edu/merrill/text/papers/pebbleinthepond.pdf