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© [email protected], 9/21/2007 1
Auralog Project
Automation and Integration
DRAFT TRP, Language Lab 397
Auralog Summary Slide
• Pros• Alternatives• Issues and Workarounds
– Accounts– Content Search– Learning Path Creation
• Syllabus integration
© [email protected], 9/21/2007 2
DRAFT TRP, Language Lab 398
Reviews• Bunting (2004), Lafford (2006), Lickey (2006),
Reeser (2006), Zheng (2006)– PROS:
• technology, esp. speech recognition – Which can be tricked, but used in a blended setting, will get
your students to speak already during class prep • considerable pedagogy
– “lack of cultural [authentic] content”, due to content reuse – → cohesion for easier management across esp. western
languages: Arabic, British English and American English, Chinese, Dutch, French, German, Italian, Japanese
– CONS: Unclear relation to a taught course, not extensible by own content
• Except for loosely linked “extra activities”
DRAFT TRP, Language Lab 399
1Auralog Pros: Content• Structured delivery and progression in chapter-
like units (structures and vocabulary and chapters building on each other)
• Multimedia-rich• All 4 skills, including speech recognition, text
transformation writing tasks• Auto-correcting and self-grading• Chance to transform at least the homework
part of your learning in one step: replace “pulp”-by i-learning
© [email protected], 9/21/2007 3
DRAFT TRP, Language Lab 78
Auralog: Training Example: Speech Recognition
• Use the general help• Observe the speak/listen cues on top of the screen• Example Video
DRAFT TRP, Language Lab 401
2Auralog Pros: Infrastructure
• (somewhat) searchable/browsabledatabases of
• Stakeholders (Students, Tutors, Groups)• Content (Learning materials, Student language
output: Autograding, Reporting (including effortless student audio recordings, exportation for data mining), Record keeping
– Messaging system (used also assigning)
© [email protected], 9/21/2007 4
DRAFT TRP, Language Lab 402
Exercise-Making, Pin-Making• Adam Smith’s Division of Labor on the verge of
the information revolution: what is a cottage industry?– Automate through NLP
• if you can work beyond regular expressions– Crowdsource
• if you have a network that is more than hardware, but can also parcel out
– Centralized content providers• Localized interaction with student and intelligent processing
of the resulting data• JISC statement that US content creation is largely owned to
publishing houses?
DRAFT TRP, Language Lab 403
1Auralog Alternatives
• Textbook publishers– Blackboard cartridges (for textbooks with
mainly assessments)– Quia.com:
• + Integration of homework and in-class• - Separate infrastructure, simplistic• - Simple transformation of paper/tape listening
content • - No recording of student output students not
speaking
© [email protected], 9/21/2007 5
DRAFT TRP, Language Lab 404
2Auralog Alternatives
• Learning Object Repositories Merlot (US), Jorum (UK): – Limited quantity (in the 100s/12s), limited
search, learning “objects” to be integrated into a progression, and into a data-processing infrastructure
– Steep Requirements: collaborative tagging infrastructure; metadata schemas; controlled vocabularies; taxonomies; facet analysis; ontologies
DRAFT TRP, Language Lab 405
Accounts I: Default• Integration with HE student information systems (Aston: SITS) not
on par with VLEs (Aston: Blackboard)– Have students create their own accounts? See Anti-pattern– Batch Account creation/ Importation Tool
• Fails on duplicates, No updates possible• No support for 1student-1enrolment-records, but ~60% of student enrolment
in a 2nd, 3rd or higher-numbered language module ((2006 TP1)).• Problem: how can instructors easily connect to their students?
– a student can be paired only with one “tutor” per target language at a time
– Workaround: instructors as super-tutors (with “access to all studentgroups”), and interaction of instructors with their subsets of students through filtering by studentgroups
• New problem: students can belong to only 1 studentgroup per studentgrouptype– Workaround: create 1 studentgrouptype per studentgroup = module
© [email protected], 9/21/2007 6
DRAFT TRP, Language Lab 406
Accounts II: Studentgroups
• Attempt to pre-create through autoitall unique studentgroups (with studentgrouptypes) (year, term, module, group) for the forseeablefuture – App hangs at about 30000
studentgrouptypes (< ∞, but auralogrestored our database free of charge)
• give up on 1 account per student and on sub-groups (sections), instead create yearly student accounts, assign those at year/teaching period start to permanent modules (studentgroups/studentgrouptypes), add new modules (few) manually
DRAFT TRP, Language Lab 407
Accounts III: Studentgroups
• Default tedious
• Automation
© [email protected], 9/21/2007 7
DRAFT TRP, Language Lab 408
Accounts IV: Students• No LDAP integration pull in uniquenames and fake passwords• No handling of multi-record course-enrolments of a student VBA,
Lookup-functions• No uniquename for instructor, only surname and firstname use
instead uniquename, sortname
DRAFT TRP, Language Lab 409
Accounts V: Results
• Automated– creating 368
studentgrouptypes– for 368 studentgroups
= modules • Enrolled 739 students• Including in multiple
modules• Including in multiple
languages
© [email protected], 9/21/2007 8
DRAFT TRP, Language Lab 410
Content I: Default
• Default content printing interface is tedious
DRAFT TRP, Language Lab 411
Content II: Built-in• Default content search and printout
documented: Tell_Me_More_Tutor_Tools_Tools_Content_Printout.wmv
• Add-on vendor-provided Tables of Contents
© [email protected], 9/21/2007 9
DRAFT TRP, Language Lab 412
Content III:Automation• Autoit
programm
• Allows extraction of content (per language 3.402 pdf files
DRAFT TRP, Language Lab 413
Content IV:Automation• * 8 > 100,000
files• add
Solutions/Translations/GrammarLinks better course integration (emailed assignments, in-class handouts)
• Add unique ids for management
© [email protected], 9/21/2007 10
DRAFT TRP, Language Lab 80
Auralog: Content Search(Labeau)Number of matches
Help about the syntax
DRAFT TRP, Language Lab 81
Auralog Content XLS
© [email protected], 9/21/2007 11
DRAFT TRP, Language Lab 415
1Learning Path Creation
• Getting all possible paths, both– Atomic elements (up
to many questions)– And cross-section
collections on the multi-element exercise level and activity type level (e.g. all dialogues per level)
DRAFT TRP, Language Lab 416
2Learning Path Creation
• Setting: In Progress • Extract Content,
export to Excel: – instructors filter
relevant learning paths by content and student recipients, refer students to unique id
© [email protected], 9/21/2007 12
DRAFT TRP, Language Lab 417
3Learning Path Creation
• Automate the importation of instructor-rearranged pdf-files
DRAFT TRP, Language Lab 419
An Auralog Syllabus Addition
• Topical Learning Paths for remedial study
© [email protected], 9/21/2007 13
DRAFT TRP, Language Lab 420
1 Auralog Syllabus– Self-access homework preparation
• “auto-correction of errors without the fear of instructor judgment. This is a particular advantage in the area of oral skills, which students so often want to master yet most fear practicing in a classroom setting.”
– Face-to-face class work• Bring computer exercises to class for review (extra lap?) • Bring pdf printouts to class for application
– Reese (2006): “The program might best be conceived of as a step in a communicative approach, where students might subsequently create freely with the language targeted as building blocks of dialogues or other discursive forms.”
• Would also benefit from non-Auralog, but content-aligned “extra activities”
DRAFT TRP, Language Lab 421
2 Auralog Syllabus
• Adaptive Learning Paths: Prep all, 2/3 all,1/3 extra for weak
ExerciseType Skill Seq AssignedGrammar Explanations G all:prepGlossary V all:prepThe Right Word V 1 all:regWord Association V 2 all:regMystery Phrase V 3 all:regWord Order R;W- all:regGrammar Practice G all:regText Transformation G;R;W all:regVideo L all:regVideo MCQ L;R- all:regFill-in-the-Blanks V;G all:regDialogue L;R-;S all:regSentence Practice G weakWords and Functions G weakDictation G-;L;V- weakPicture&Word Association V weakWords and Topics V weak
© [email protected], 9/21/2007 14
DRAFT TRP, Language Lab 422
3 Auralog Syllabus
• Example German– Example intermediate “family”=level: 12
“units”=chapters, subdividable into 3*(2*2 related) topics
– 1 “unit”=chapter per class hour → 2 per week – 6 weeks per “family”=level → 2 levels per 12-
week teaching period → including 3 business levels, 2.25 years for ab initio UWLP
DRAFT TRP, Language Lab 68
Teacher monitors student output (audio) and self-graded resultsAuralog
Teacher builds (once) custom learning paths
Auralog Use in Detail IAutograding > threshold?
Tutortools / Student accounts:Results
Before Face-face Class At End of Teaching Period
Face2Face Class
Final Grade
Adaptive Regular
Progressive Chapters, divided into Levels, for weekly lab homework
Observed Weaknesses?
Topical (primarily Structures, e.g.
Subjunctive)
Built-in
Progressive ChaptersTopical
Fast Lane Extra Lap
AuralogTable of
content.doc
M:Auralogcontent
.xls pdf
Desktop Search against Content Printout
All:Prep
AuralogPDFs
© [email protected], 9/21/2007 15
DRAFT TRP, Language Lab 423
1Auralog Hacks
• Mute Sound– By altering these sound files in a sound editor– Here unobtrusive jingle (52kb) for sound testing
DRAFT TRP, Language Lab 424
2 Auralog Hacks
• Accessibility– The student (adobe flash) application is
notorioulsy inaccessible (tested with screenreader)
– Not so the content printouts