Learner certitude/confidence (motivation)
Capacity of decisions across layers (deisgn)
Matching feedback types to situation
1. Progress feedback, goal orientation (feedback)
2. Take advantage of dual-coding when relevant (cognition)
3. Manage cognitive overload, avoid split attention (cognition)
4. Chunking 7+/-2 (cognition)
5. Analysis drives design choices; alignment (design)
6. Usability of design (design); Contiguity effect
7. Exploit openess to maximize access to content, minimize user effort on generation, share and compare results (design, learner control)
8. Utilize spacing effect, lag (practice)
9. Maximize ALT – academic learning time (practice)
11. Expanded reshearsal schedule (Leitner) (practice)
12. Timing of feedback (feedback)
13. Structure +/- low level students; (13 & 11) prior knowledge; Tracking (see 1, 13, 11) (design)
14. ARCS – Attention, relevance, confidence, satisfaction (motivation) (design)
15. Learner control, allow for, Learner as agent
Increase channel capacity (cognition)
==Design==
Prototyping (more than 1) (design)
Bloom’s taxononmy (design)
Reflection of environment (design)
Tutoring
2-sigma, more knowledgeable other, vygotsky’s ZPD
The List
“a list of principles for effectively and efficiently teaching facts and a supporting rubric for ”
5. (things from paper, with page number)
Analysis drives design choice
prior knowledge
openness
The Program…
#* Determines learner’s prior knowledge. (summative)
#** Pre-assesses learner’s prior knowledge to determine topics and items (summative)
#**Pre-assessment may be the first iteration of Leitner system. Prior knowledge can inform second iteration of Leitner system repetitions. (Wikipedia, Leitner system)
#* Consider prior knowledge to determine type of feedback.
#** (Mason & Bruning 15-16, 21) (high = topic contingent; low = response contingent; requires categorizing of learners according to pre-assessment, or granular correlation of practice items with pre-assessment items)
#* Facilitates open content
#** Allows for user-generated content.
#** Allows user sharing of content.
#** Allows user sharing of results.
#** Allows user comparions of results.
===Notes===
Mason & Bruning. Providing Feedback in Computer-Based Instruction: What the Research Tells Us
Considering the students’ level of prior knowledge allows the program to effectively implement verification or elaboration (15)
Feedback must go beyond “simple judgment of the correctness of their response” or “answer-until-correct”.
“If students have relatively little prior knowledge, knowledge-of-correct-response with response-contingent feedback will help them identify the correct answer and will assist them in determining why the selected answer was incorrect. … [it] allows them to concentrate on the specific erorr as opposed to more general misunderstandings. On the other hand if students have a solid knowledge base, knowledge-of-correct-respons with topic-contingent feedback not only will identify the correct answer but allow them to review relevant material so that they may determine where their error was made.” (15)
“To the extent that students possess relevant prior knowledge, they are more likely to make effective use of the instructional material since they have a base of information from which to relate and apply the information.” (15)
“Higher achieving students possessing larger knowledge bases may benefit more from feedback providing general information and allowing them to reevaluate their own answers.” (16)
Degree of prior knowledge may lead to different types of feedback or levels of evaluation: Low prior knowledge should be followed by knowledge-of-correct-response with response-contingent; high prior knowledge should be followed by knowledge-of-correct-response with topic-contingent. (21)
==Feedback==
Tie feedback and relate responses to learner’s goals.
Periodic feedback based on tracked data correlated to learner goals.
IPT 564 Notes 07-15-2010
Learner certitude/confidence (motivation)
Capacity of decisions across layers (deisgn)
Matching feedback types to situation
1. Progress feedback, goal orientation (feedback)
2. Take advantage of dual-coding when relevant (cognition)
3. Manage cognitive overload, avoid split attention (cognition)
4. Chunking 7+/-2 (cognition)
5. Analysis drives design choices; alignment (design)
6. Usability of design (design); Contiguity effect
7. Exploit openess to maximize access to content, minimize user effort on generation, share and compare results (design, learner control)
8. Utilize spacing effect, lag (practice)
9. Maximize ALT – academic learning time (practice)
11. Expanded reshearsal schedule (Leitner) (practice)
12. Timing of feedback (feedback)
13. Structure +/- low level students; (13 & 11) prior knowledge; Tracking (see 1, 13, 11) (design)
14. ARCS – Attention, relevance, confidence, satisfaction (motivation) (design)
15. Learner control, allow for, Learner as agent
Increase channel capacity (cognition)
==Design==
Prototyping (more than 1) (design)
Bloom’s taxononmy (design)
Reflection of environment (design)
Tutoring
2-sigma, more knowledgeable other, vygotsky’s ZPD
The List
“a list of principles for effectively and efficiently teaching facts and a supporting rubric for ”
5. (things from paper, with page number)
Analysis drives design choice
prior knowledge
openness
The Program…
#* Determines learner’s prior knowledge. (summative)
#** Pre-assesses learner’s prior knowledge to determine topics and items (summative)
#**Pre-assessment may be the first iteration of Leitner system. Prior knowledge can inform second iteration of Leitner system repetitions. (Wikipedia, Leitner system)
#* Consider prior knowledge to determine type of feedback.
#** (Mason & Bruning 15-16, 21) (high = topic contingent; low = response contingent; requires categorizing of learners according to pre-assessment, or granular correlation of practice items with pre-assessment items)
#* Conduct audience analysis to ensure objectives meet learner needs, content complements learner prior knowledge, and design meets learner abilities/preferences (design)
#**(ADDIE)
#* Determines learner’s motivation profile, learning goals, modifiable influences, etc. (summative)
#**(Keller 3-6 ARCS)
#* Facilitates open content
#** Allows for user-generated content.
#** Allows user sharing of content.
#** Allows user sharing of results.
#** Allows user comparions of results.
===Notes===
Mason & Bruning. Providing Feedback in Computer-Based Instruction: What the Research Tells Us
Considering the students’ level of prior knowledge allows the program to effectively implement verification or elaboration (15)
Feedback must go beyond “simple judgment of the correctness of their response” or “answer-until-correct”.
“If students have relatively little prior knowledge, knowledge-of-correct-response with response-contingent feedback will help them identify the correct answer and will assist them in determining why the selected answer was incorrect. … [it] allows them to concentrate on the specific erorr as opposed to more general misunderstandings. On the other hand if students have a solid knowledge base, knowledge-of-correct-respons with topic-contingent feedback not only will identify the correct answer but allow them to review relevant material so that they may determine where their error was made.” (15)
“To the extent that students possess relevant prior knowledge, they are more likely to make effective use of the instructional material since they have a base of information from which to relate and apply the information.” (15)
“Higher achieving students possessing larger knowledge bases may benefit more from feedback providing general information and allowing them to reevaluate their own answers.” (16)
Degree of prior knowledge may lead to different types of feedback or levels of evaluation: Low prior knowledge should be followed by knowledge-of-correct-response with response-contingent; high prior knowledge should be followed by knowledge-of-correct-response with topic-contingent. (21)
==Feedback==
Tie feedback and relate responses to learner’s goals.
Periodic feedback based on tracked data correlated to learner goals.
System allows