1. adaptive evalutation
1.1. evaluation
1.1.1. predictive
1.1.2. formative
1.1.2.1. avoid acquired impotence (link)
1.1.3. n / a mmative
1.2. continuous evaluation
1.2.1. from activities
1.2.2. without summative evaluation
1.2.3. shortening trees
1.2.3.1. Pix
1.3. feedback
1.3.1. automated
1.3.1.1. offered to students
1.3.1.2. coaching link student
1.3.2. semi automated
1.3.2.1. offered to teachers
1.4. Analysis of collaborative practices
1.5. scoring/assessment
1.5.1. semi automated
1.5.2. automated
1.6. reorientation
1.6.1. explicability ??
1.6.2. see Paces Grenoble
1.7. examples
1.7.1. Pix
1.7.2. PACES Grenoble
1.7.3. ...
2. interaction textual
2.1. chatbot
2.2. uses natural language processing
2.2.1. understanding
2.2.2. sematic analysis
3. various disorders diagnosis
3.1. disorders
3.1.1. Dys
3.1.2. ASD
3.1.3. ...
3.2. On weak signals
3.3. identification from traces of activities
3.3.1. including textual
3.3.2. productions including oral productions
3.4. ...
4. coaching students
4.1. learning behaviors
4.1.1. organized tion
4.1.1.1. procrastination
4.1.1.1.1. nudging
4.1.1.2. task planning
4.1.1.3. mémorisaiton
4.1.1.3.1. curve of forgetting
4.1.2. engagement
4.1.2.1. objectives
4.1.2.2. nudging
4.1.3. vision of the future
4.1.3.1. direction
4.1.3.2. commitment
4.1.4. anticipation dropping
4.1.4.1. on weak signals
4.2. guidance
4.2.1. probable trajectories
4.2.1.1. choices
4.2.1.2. corrective measures
4.2.2. choices
4.2.2.1. Corrective measures
5. Increase of documents
5.1. Examples
5.1.1. Google Doc
5.1.1.1. Voice
5.1.1.2. input Grammatical correction
5.1.1.3. Addition of illustrations
5.1.1.4. Translation
5.1.2. Google Sheet
5.1.2.1. Proposes formulas
5.1.2.2. Proposes cross sorting
5.1.2.3. Offers dataviz
5.1.2.4. translation
5.1.3. Google Slide
5.1.3.1. Voice input of slides comments input
5.1.4. Excel
5.1.4.1. Automatic analysis of tables
5.1.4.2. from a photo
5.1.5. equation solving tool
6. Text correction
6.1. Spelling
6.2. Grammar
6.3. translation of bad French into good French ...
7. security management
7.1. adaptive filtering
7.2. See Parents in the area, Witigo, Block.si
7.2.1. to the individual
7.2.2. by geolocation
7.2.3. by content analysis
7.3. cyber harassment prevention
7.4. see Blocksi (fr) SmoothWall or GoGardian
7.4.1. victim
7.4.2. identification author identification
7.5. prevention radicalization
7.6. see Witigo (fr)
7.7. prevention of negative behavior
7.8. see Block.si
7.9. facial recognition
7.9.1. access management in the establishment
7.9.2. see 2 lycées ac Nice and Marseille
7.9.3. management of the call at the start of the course
7.10. sound listening
7.11. takes up the idea of 舃Saint Etienne (and many American cities): the establishment is already sound. We add microphones on the speakers. Listening (without permanent recording) detects "abnormal" signals (noise at night, fights, insults, intrusions, ...) and locates by triangulation the fact in progress to allow faster human intervention. A recording of the previous 3 minutes can also be considered, which implies another architecture. See the ethical aspects and RGPD (recognition of people for example?)
7.11.1. See Ville de Saint Etienne (link)
7.11.2. produced by Serenicity (link)
8. SI management
8.1. attack detection
8.2. machine loads Optimization
8.3. data center Optimization
8.3.1. air conditioning
8.3.2. electrical consumption
8.3.3. anticipation Maintenance
8.3.4. Anticipation hardware
8.4. detection flaws
8.4.1. mobile application
8.4.2. applications coded
8.5. optimizationIaaS PaaS and SaaS
9. semanticization of texts
10. automated summaries
10.1. examples
10.1.1. SummarizeBot (link)
11. image recognition
11.1. Recognition of fake diplomas
11.2. handwriting
11.3. drawing
11.4. OCR
11.5. examples
11.5.1. Jamboard Google
12. search engines
12.1. Delve on 365
12.2. CloudSearch on GSuite
13. Definition (link)
14. Teach AI! (link)
14.1. Big data
14.2. articulation Dataviz articulation
14.3. Discovery of the principles
14.4. Issues, hopes and fears
14.4.1. EMI
14.4.2. Digital culture
14.4.3. foresight scenarios
14.5. Discovery and treatment of biases
14.5.1. MachineLearningForKids
14.6. chatbot programming
14.6.1. Complexity
14.6.1.1. Simple decision tree
14.6.1.2. Request by call for services
14.6.2. usable tools
14.6.2.1. SAP (ex recast.ai)
14.6.2.1.1. GitHub account
14.6.2.1.2. Free Prototype
14.6.2.2. MachineLearningForKids (link)
14.7. Deep learning
14.7.1. programming Tensorflow.js type
14.7.2. example on
15. adaptive learning adaptation
15.1. of activities
15.1.1. choice of the following activity
15.1.2. course over several sessions
15.1.3. research balance
15.1.3.1. challenge
15.1.3.1.1. sufficiently motivating
15.1.3.2. probable success
15.1.4. examples
15.1.4.1. Kwyk
15.1.4.1.1. math exercises
15.1.4.2. Lalilo
15.1.4.2.1. learning grapheme / phoneme
15.1.4.3. Glossary
15.1.4.3.1. adaptive reader adaptation
15.2. of content
15.2.1. by recommendation
15.3. memory anchoring
15.3.1. identification of the forgetting cycle
15.3.2. adaptation of the recall rhythm
15.3.3. examples
15.3.3.1. Wonoz
15.3.3.2. Orthodidacte
15.3.3.3. Bescherelles
15.3.3.4. Frantastique
16. voice interaction
16.1. transcription pronounced sentences
16.1.1. speech2text input
16.1.2. Voice
16.1.3. Automatic subtitling
16.1.3.1. Almost real time
16.2. oral restitutions
16.2.1. text2speech
16.3. handicap
16.3.1. application pictogram
16.3.2. translation in LSF
16.3.3. voice input of texts
16.4. hands on another task
16.4.1. Technical training
16.5. Simultaneous translation
16.5.1. Skype
16.6. examples
16.6.1. chatbot
17. pairing
17.1. pairing content
17.1.1. recommendation
17.1.2. video
17.1.2.1. Youtube
17.1.2.1.1. content provided by peers
17.1.2.2. Netflix
17.1.2.2.1. contents provided by editors
17.2. pairing individuals
17.2.1. peers for teamwork
17.2.1.1. Between students
17.2.1.2. Between
17.2.2. mentor or coach
17.2.2.1. students
17.2.2.1.1. peer
17.2.2.1.2. teachers
17.2.2.1.3. mentor
17.2.2.2. For Teachers
17.2.2.3. For executives
18. stall diagnosis
18.1. based on school life data
18.1.1. delays and absences
18.1.2. comments
18.1.2.1. teachers
18.1.2.2. school life
18.1.3. evolution of grades
18.1.4. implication in facts
18.1.4.1. as perpetrator
18.1.4.2. as victim
18.1.5. sanctions
18.1.6. passage infirmary
18.1.6.1. attention given potentially sensitive
18.2. suggestion of remediation
18.2.1. based on the previous trajectories of pupils
19. Attitude / behaviors Detection
19.1. attention and commitment
19.1.1. position
19.1.2. activity
19.1.2.1. Reading
19.1.2.2. Production
19.1.3. of facial expression
19.1.3.1. Detection of emotion
19.2. means
19.2.1. video
19.2.2. oculometry
19.2.3. sensors on seats
19.2.4. monitoring of movements
19.2.4.1. as in rugby
19.2.5. Text analysis
19.2.5.1. Detection of emotion
19.3. for
19.3.1. student
19.3.2. teachers
19.3.2.1. supervision
19.3.2.2. see example of sowing videos of supervision in Great Britain (seen at BETT 2019)
20. system management
20.1. results prediction
20.1.1. by cohort
20.1.2. by establishment
20.1.3. by sector
20.1.4. Examples
20.1.4.1. Great Britain (seen at Bett)
20.2. HR prediction
20.2.1. absences
20.2.1.1. Anticipation
20.2.2. replacement
20.2.2.1. Anticipation
20.2.2.2. optimization
20.2.3. Training
20.2.4. Career trajectory
20.2.4.1. See student orientation!
20.3. Optimization of EdT
20.4. Optimization of school card measures
20.4.1. Opening
20.4.2. Closing
20.4.3. Transformation
20.5. identification of pbs various
20.5.1. syllabuses
20.5.2. program
20.5.3. activities
20.5.4. evaluations
20.5.5. suitability skills
20.6. Optimization of resources
20.6.1. Exam management (oral)
20.6.1.1. See Nancy
21. GRH / GPEC
21.1. recruitment of
21.1.1. teachers
21.1.1.1. in emergency phase
21.1.1.1.1. contractual
21.1.2. executives
21.1.2.1. by profile monitoring
21.2. initial
21.3. training continuing training
21.3.1. offer of training tailored
21.3.2. monitoring skills
21.3.2.1. badges
21.4. supervision / mentoring
21.4.1. pairing
21.4.1.1. mentor / teacher
21.4.1.2. peer / peer
21.5. coaching professors
22. See Tellia
22.1. necessary for chatbots
22.2. evaluation of semantic richness
22.3. Syntactic structure
22.3.1. Intent
22.4. classification of texts
22.4.1. adaptive reading
22.4.1.1. to advance the reader
22.4.2. see Lexile of (link)
23. automated translations
23.1. with subtitles audio and video
23.2. type Youtube eg
23.2.1. accessibility
23.3. examples
23.3.1. Google Translate (link)
23.3.2. Bing Translator (link)
23.3.3. DeepL (link)
24. indexing content
24.1. automatic
24.1.1. image
24.1.2. texts
24.1.3. sounds
24.1.4. videos
24.2. semi automatic
24.2.1. using reinforcement
24.3. suggestion of supplements
24.4. enrichment syllabus
24.5. examples
24.5.1. PerfectMemory