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H86h4j98CrL'U^b$BČdAuV]b(#TC^$b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$y 0AA@ʚ;Q,ʚ;g45d5d-a0tppp@ <4!d!d))0L<4dddd))0L <4BdBdK*0L|___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p" ___PPT9~v ?LNov 9th 2006 Jan 5th 2005O =$?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  ?Does the online learning environment support critical inquiry ?@@? 3Few threads reached a conclusion Closer synthesizes and ends debate Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge and Generating hypotheses Open-ended debateBSPPPSS 6What interactions generate greatest student engagement77(6 IAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages generated significantly more (24 reads per message) reads than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersPJP]"I &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Ccorrelation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsFacilitation does work Students quickly identify valuable contributors Changing Contributor to Facilitator Identification of thought leaders Early stages crucial Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /%&'(*+, 0` ` ̙33` 333MMM` ff3333f` f` f` 3>?" dd@,|?" dd@   " @ ` n?" dd@   @@``PR    @ ` ` p>> f(    6$Ȩ P  T Click to edit Master title style! !  0˨   RClick to edit Master text styles Second level Third level Fourth level Fifth level!     S  0Ѩ ``  >*  0ר `   @*  0ۨ `   @*H  0޽h ? ̙33 Default Design0 zr@< (  < < 0$ P    P*   < 0t(     R*  d < c $ ?   < 0<-  @  RClick to edit Master text styles Second level Third level Fourth level Fifth level!     S < 62 `P   P*   < 67 `   R*  H < 0޽h ? ̙3380___PPT10.ߛm0  $(  r  S   r  S ،` 0   H  0޽h ? ̙33y___PPT10Y+D=' == @B +m 0  $(   r  S (þp   r  S ľ``  H  0޽h ? ̙33y___PPT10Y+D=' == @B + 0 (  r  S db b H  0޽h ? ̙3380___PPT10." 0 A(  r  S   0`   R  s *]f  C >A&CommunityofInquiryp0  6@@x aGarrison et al 2000 H  0޽h ? ̙33y___PPT10Y+D=' == @B +T 0 kc@T(  Tx T c $a@   t T C LA4CommunityofInquiry-better` T 6|@x aGarrison et al 2000 H T 0޽h ? ̙33___PPT10i. @'+D=' == @B +$ 0 $(  r  S  2  J , 2j  2.l> J ,j 8H  0޽h ? ̙33y___PPT10Y+D=' == @B + 0 F(  r  S ƶ     0ɶ`P0  425,937 individual reads of discussion board message (range 331  2179 reads per student) 951 student postings (range 1  154 per student) Most active period weeks 1 & 2 (157 posts and 162 posts) Then steady pattern of ~ 70-80 posts per week." 2H  0޽h ? ̙33y___PPT10Y+D=' == @B +m 0  $(   r  S \   r  S 4P0  H  0޽h ? ̙33y___PPT10Y+D=' == @B +} 0 p`$(  `r ` S dPp@   r ` S (p  H ` 0޽h ? ̙33___PPT10i.`2+D=' == @B +F 0 EEEAeZE(  d d c $ ;  ; D  Ae #"B6  ;L dd B;?: ~v0___PPT106___PPT9 L100.0%*(#"I cd B;? :~v0___PPT106___PPT9 I174*(#" bd B;?   @ @`I ad B ;? ~v0___PPT106___PPT9 ITOTAL( #"O `d B!;?:  ~v0___PPT106___PPT9 O60.9%.('"M _d B,;? : ~v0___PPT106___PPT9 M106.('"O ^d B,;?  ~v0___PPT106___PPT9 OFaculty, '"S ]d B00;?  ~v0___PPT106___PPT9 S Contributor,  '"O \d Bx3;?:  ~v0___PPT106___PPT9 O10.3%.('"L [d Bx>;? : ~v0___PPT106___PPT9 L18.('"S Zd BB;?  ~v0___PPT106___PPT9 S Facilitator,  '"S Yd BE;?  ~v0___PPT106___PPT9 S Facilitator,  '"N Xd BH;?:  ~v0___PPT106___PPT9 N9.2%.('"L Wd Bd BL;?   ~v0___PPT106___PPT9 O Contributor(  #"L =d B;?  ~v0___PPT106___PPT9 LEliciter(  #"J l s *1 ?P ZB ?l s *1 ?0 P0 ZB Bl s *1 ?I0 IZB Dl s *1 ?pPp ZB Gl s *1 ?P ZB Kl s *1 ?B0 BZB Xl s *1 ?;0 ;ZB el s *1 ?40 4ZB rl s *1 ?-0 -ZB l s *1 ?&0 &ZB l s *1 ?0 ZB l s *1 ? 0  E$  PH  am #"2&ffffffffP P O l B=?OPH ~v0___PPT106___PPT9 O70.1%.('"M l B=?OH ~v0___PPT106___PPT9 M122.('"O l B=? OH ~v0___PPT106___PPT9 OFaculty, '"O l B=?VPO~v0___PPT106___PPT9 O15.5%.('"L l B=?VO~v0___PPT106___PPT9 L27.('"S l B=? VO~v0___PPT106___PPT9 S Contributor,  '"O l BP=?]PV~v0___PPT106___PPT9 O14.4%.('"L l B=?]V~v0___PPT106___PPT9 L25.('"S l B=? ]V~v0___PPT106___PPT9 S Facilitator,  '"J l B=?dP]~v0___PPT106___PPT9 J0.0%*(#"G l B=?d]~v0___PPT106___PPT9 G0*(#"O l Bx=? d]~v0___PPT106___PPT9 O Complicator(  #"J l Bp=?kPd~v0___PPT106___PPT9 J0.0%*(#"G l B=?kd~v0___PPT106___PPT9 G0*(#"J l Bl=? kd~v0___PPT106___PPT9 JCloser( #"J l B=?rPk~v0___PPT106___PPT9 J0.0%*(#"G l B4=?rk~v0___PPT106___PPT9 G0*(#"L l B=? rk~v0___PPT106___PPT9 LEliciter(  #"J l Bh=?yPr~v0___PPT106___PPT9 J0.0%*(#"G l B=?yr~v0___PPT106___PPT9 G0*(#"P l BDI? yr~v0___PPT106___PPT9 P Acknowledger(  #" l B| I?Py @ @` l B\I?y @ @`O l BI? y~v0___PPT106___PPT9 O Receivers*  #"ZB l s *1 ? PZB l s *1 ? H PH ZB l s *1 ?  H ZB l s *1 ?PPH ZB l s *1 ? yPyZB l s *1 ?H ZB l s *1 ?H ZB l s *1 ? rPrZB l s *1 ? kPkZB  m s *1 ? dPdZB m s *1 ? ]P]ZB &m s *1 ? VPVZB 3m s *1 ? OPO Rn 0I ` jRatio of receive to send Contributor = 27/106 = 0.25 Facilitator = 25/38 = 0.65 Complicator = 0/17 = 0.002kH l 0޽h ? ̙33___PPT10i.p +D=' O= @B + 0  p(  pr p S (I  I L p C $A week3 * R p S *A week6 : L p C $A week9z PU p 0h=0 P  ?Week 3 (n = 63) 2 p 0=0 P  = Week 6 (n=51) 2  p 0<=   ?Week 9 (n = 60) 2H p 0޽h ? ̙33___PPT10i.Уā+D=' O= @B +$ 0 t$(  tr t S |AIp  I r t S TBIP0 I H t 0޽h ? ̙3380___PPT10.pv'$ 0 x$(  xr x S NI`  I r x S (SI I H x 0޽h ? ̙3380___PPT10.k 0 ~v|(  |r | S dI  I \ | C 4AreadfrequencypH | 0޽h ? ̙3380___PPT10.P˕$ 0 $(  r  S 4jI0  I r  S  kI0 ` I H  0޽h ? ̙3380___PPT10.PM$ 0 $(  r  S {I`  I r  S |I` I H  0޽h ? ̙3380___PPT10.ૢg$ 0 $(  r  S IP  I r  S XI I H  0޽h ? ̙3380___PPT10.:$ 0  $(  r  S LIP  I r  S $I I H  0޽h ? ̙3380___PPT10.@mU$ 0 0$(  r  S |IP  I r  S TI I H  0޽h ? ̙3380___PPT10. i 0 p0$(  0r 0 S v   r 0 S    H 0 0޽h ? ̙33W 0 `4(  4r 4 S I  I r 4 S I@ I  4 6tI  ] Limitations    4 0I  @Influence of prior online learning-experience on patterns of behavior Larger sample size Deeper analysis of content Explore vicarious learning contributions more fully Explore why patterns change Compare ill-defined vs. well-bounded questions.  !!H 4 0޽h ? ̙33j 0 P8(  8r 8 S I  I H 8 0޽h ? ̙330 zr0@ (  @X @ C <   r @ S  < @   H @ 0޽h ? ̙330 ~@(  X  C <   H~  S H< @  H A key problem facing educators is that of maintaining student engagement. For online learning this problem can be more acute. Physical separation from instructors and peers can lead to problems such as alienation, lack of commitment and antisocial behavior. H  0޽h ? ̙3380___PPT10.<]0 pm(  X  C <     S H< @   o[One model of the community of inquiry can be found in the work of Garrison, Anderson, Archer and colleagues in Athabasca. This model emphasizes the importance of three different presences required for a community of inquiry, namely social, cognitive and teaching. When all these elements are available a process of Critical Inquiry can take place.H  0޽h ? ̙3380___PPT10.tY0 f^(  X  C <   O^  S "O< @  O I took as my starting point the community of inquiry construct. Loosely speaking the Community of inquiry construct has its roots in pragmatism Dewey (1916). Inquiry is a collaborative activity building on multiple perspectives.H  0޽h ? ̙3380___PPT10.`xh0 ph(  X  C <   Oh  S `O< @  O &The Initiator creates a social network by looking for points of connection between members and draws participants out. A Contributor adds to debate in terms of a contractual obligation. The Facilitator maintains impetus in debate by acknowledging useful contributions and drawing out debate. A Peer-Knowledge-Elicitor seeks information regularly. A Vicarious Acknowledger ( me-too ) demonstrates recognition that another contribution influenced their perspective. A Complicator forces the community to reflect on assumptions and suggests alternative interpretations, they point out inconsistencies in arguments and may reframe questions. A Closer attempts to pull together a final coherent answer by synthesizing difference perspectives. The Passive Learner makes no overt contribution.. l : ] ^ ` H  0޽h ? ̙3380___PPT10. P0 zr (  X  C <   Or  S O< @  O The role was derived based solely on the content of the message not on its position in the thread or what preceded or followed it. So when I say facilitation it miter be better to call it attempted facilitation as like oysters not all of them work.H  0޽h ? ̙3380___PPT10.R0 b(  X  C <   O  S O< @  O dPIf we look at the senders of messages we see as expected that most messages are of the contractual obligation types, but there is a small but healthy number of facilitator type messages and a notable number of complicator messages. In terms of receivers the Instructor is the biggest recipient. When we consider response rate as a percentage of send rate we see that although the contributor message type is very common it is far less likely to generate a response than the facilitator message. The lack of response to complicator messages is an artifact that I want to examine more closely.H  0޽h ? ̙3380___PPT10.0 jb(  X  C <   Ob  S hO< @  O There are some dyads that are consistent across time. however the patterns do change from week to week. The complicator role is more active in week 9. Messages in later weeks are more likely to be responses to peer messages rather than responses to the faculty member s posts. The raw number of posts per week does not decline significantly over time."6 ) H  0޽h ? ̙3380___PPT10.f*rPj.=?C@G6{}v!G#s%'AJ3X69<JEHLQ,1z/( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ" DWingdingsRomanLLԖ-a0ԖOn-screen ShowDrexel Universityk  Times New RomanArial WingdingsDefault Design@Determinants of Engagement in an Online Community of Inquiry BackgroundSlide 3Community of Inquiry Cycles of Inquiry %Building on the Garrison et al ModelStudent RolesResearch QuestionsStudy Raw results Student behaviorDetailed AnalysisKAre there noticeable patterns of interactions between participant roles? Slide 14-Do patterns of interaction change over time?@Does the online learning environment support critical inquiry ?@Does the online learning environment support critical inquiry ?7What interactions generate greatest student engagement'Who are the most attended to posters ?%Why are some posters more engaging ?1Is frequency of posting related to popularity? 0Does length of message relate to read frequency3Does position of message affect frequency of reads3Does type of participant affect frequency of reads Conclusions Future Work Questions?  Fonts UsedDesign Template Slide Titles 2 )E Jim Waters 6_Gjwatersjwatersimes New Roman-. K2 1-College of Information Science and Technology  @@`` ld2<%     BS  !"#$'()*+,-./`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0tppp@ <4!d!d))0L<4dddd))0L <4BdBdK*0L|___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p" ___PPT9~v ?LNov 9th 2006 Jan 5th 2005O =%?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?DsPP+Ps+s -6What interactions generate greatest student engagement77(6 IAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages generated significantly more (24 reads per message) reads than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersPJP]"I &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Ccorrelation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. 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Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? PFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ?DsZZZss 6What interactions generate greatest student engagement77(6 IAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages generated significantly more (24 reads per message) reads than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersPJP]"I &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Ccorrelation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsFacilitation does work Students quickly identify valuable contributors Changing Contributor to Facilitator Identification of thought leaders Early stages crucial Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /%&'(*+,9 0 PH(  r  S  `   t  C LA4CommunityofInquiry-better` R  C *Acyclical`X  C 0Astahl-model` !H  0޽h ? ̙33___PPT10i.=+D=' = @B +} 0 t$(  tr t S |AIp  I r t S TBIP0 I H t 0޽h ? ̙33___PPT10i.pv'+D=' = @B +rR-GR -1/( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ" DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  !"#$&'()*+,-./0123456789:;<Oh+'0 `h    (4<HStrategies Employed By Participants In Virtual Learning Communities Drexel Universityjwaters79Microsoft PowerPoint@qj@ւ@9Gg  K  y--$xx--'@Times New Roman-. 2 q Nov 9th 2006."System-@Times New Roman-. 33C2 (Determinants of Engagement in an Online .-@Times New Roman-. 33%2 -Community of Inquiry.-@Times New Roman-. 2 )E Jim Waters 6.-@Times New Roman-. K2 1-College of Information Science and Technology.-@Times New Roman-. !2 8=Drexel Universityi.-@Times New Roman-. 2 @C Philadelphia.-@Times New Roman-.  2 O5j.-@Times New Roman-. (2 O6ames.waters@drexel.edu.-՜.+,0     5MZ   ConclusionsFacilitation does work Students quickly identify valuable contributors Changing Contributor to Facilitator Identification of thought leaders Early stages crucial Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /%&'(*+,} 0 t$(  tr t S |AIp  I r t S TBIP0 I H t 0޽h ? ̙33___PPT10i.pv'+D=' = @B +rQ-o-1/( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ" DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  @@`` ld2<%     BS  !"#$'()*+,-./`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0tppp@ <4!d!d))0L<4dddd))0L <4BdBdK*0L|___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p" ___PPT9~v ?LNov 9th 2006 Jan 5th 2005O =%?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?DsPP+Ps+s -6What interactions generate greatest student engagement77(6 IAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages generated significantly more (24 reads per message) reads than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersPJP]"I &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Ccorrelation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsFacilitation does work Students quickly identify valuable contributors Changing Contributor to Facilitator Identification of thought leaders Early stages crucial Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /%&'(*+,rD-1/( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ" DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  @@`` ld2<%     BS  !"#$'()*+,-./`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0tppp@ <4!d!d))0L<4dddd))0L <4BdBdK*0L|___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p" ___PPT9~v ?LNov 9th 2006 Jan 5th 2005O =%?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?tOPPPP+PO+s -6What interactions generate greatest student engagement77(6 IAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages generated significantly more (24 reads per message) reads than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersPJP]"I &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Ccorrelation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsFacilitation does work Students quickly identify valuable contributors Changing Contributor to Facilitator Identification of thought leaders Early stages crucial Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /%&'(*+,} 0 t$(  tr t S |AIp  I r t S TBIP0 I H t 0޽h ? ̙33___PPT10i.pv'+D=' = @B +rxAT-1 0( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ" DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  @@`` tl3?&     BS  !"#$'()*+,-./0`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0tppp@ <4!d!d))0L<4dddd))0L <4BdBdK*0L|___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p" ___PPT9~v ?LNov 9th 2006 Jan 5th 2005O =&?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?tOPPPP+PO+s -6What interactions generate greatest student engagement77(6 XAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages (asking questions) generated significantly more (24) reads pre message than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersfYP]"X &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Ccorrelation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsFacilitation does work Students quickly identify valuable contributors Changing Contributor to Facilitator Identification of thought leaders Early stages crucial Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /%&'(*+,.$ 0 x$(  xr x S NI`  I r x S (SI I H x 0޽h ? ̙3380___PPT10.k0  (  X  C <      S < @   xSo I went back to the whole body of messages and looked at the extent to which different message types were attended to.Y H  0޽h ? ̙3380___PPT10.VrM.@OQ.120( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ" DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  @@`` |t4B'     BS  !"#$'()*+,-./01`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0tppp@ <4!d!d))0L<4dddd))0L <4BdBdK*0L|___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p" ___PPT9~v ?LNov 9th 2006 Jan 5th 2005O =&?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?tOPPPP+PO+s -6What interactions generate greatest student engagement77(6 XAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages (asking questions) generated significantly more (24) reads pre message than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersfYP]"X &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Correlation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent post      !"#$%&'()*+,-./0123456789:;<=>?@ABCDEFGHIJKLMNOPQRSTUVWXYZ[\]^_`abcdefghijklmnopqrstuvwxyz|}~er posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsPeer Facilitation does work Students quickly identify valuable contributors Early stages crucial Changing Contributor to Facilitator Identification of thought leaders Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /%&'(*+,./ g  0 ~v|(  |r | S dI  I \ | C 4AreadfrequencypH | 0޽h ? ̙33___PPT10i.P˕+D=' = @B +$ 0 $(  r  S {I`  I r  S |I` I H  0޽h ? ̙3380___PPT10.ૢg 0 p0$(  0r 0 S v   r 0 S    H 0 0޽h ? ̙33 0 =5`4(  4r 4 S I  I r 4 S I@ I  4 6tI  ] Limitations    4 0I  vInfluence of prior online learning-experience on patterns of behavior Larger sample size Deeper analysis of content Explore vicarious learning contributions more fully Explore why patterns change Compare ill-defined vs. well-bounded questions.T |?    !!H 4 0޽h ? ̙330 5-(  X  C <   -  S  < @   Participant 11 is read almost twice as frequently as participant 14, 1.79 times ore often to be precise. The average reads per message for all participants is 16 reads per messageH  0޽h ? ̙3380___PPT10.%r, R Z Ʉ/v Q3/120( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ" DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  @@`` |t4B'     BS  !"#$'()*+,-./01`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0tppp@ <4!d!d))0L<4dddd))0L <4BdBdK*0L|___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p" ___PPT9~v ?LNov 9th 2006 Jan 5th 2005O =&?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?tOPPPP+PO+s -6What interactions generate greatest student engagement77(6 XAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages (asking questions) generated significantly more (24) reads pre message than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersfYP]"X &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Correlation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsPeer Facilitation does work Students quickly identify valuable contributors Early stages crucial Changing Contributor to Facilitator Identification of thought leaders Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /%&'(*+,./ r g/120( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ" DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  @@`` |t4B'     BS  !"#$'()*+,-./01`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0tppp@ <4!d!d))0L<4dddd))0L <4BdBdK*0L|___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p" ___PPT9~v ?LNov 9th 2006 Jan 5th 2005O =&?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?tOPPPP+PO+s -6What interactions generate greatest student engagement77(6 XAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages (asking questions) generated significantly more (24) reads pre message than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersfYP]"X &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Correlation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsPeer Facilitation does work Students quickly identify valuable contributors Early stages crucial Changing Contributor to Facilitator Identification of thought leaders Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /%&'(*+,./ r 3/1x0( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  @@`` 6J)     BS  !"#$'()*+,-./ 0123`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0jppp@ <4!d!d))0LЀ<4dddd))0LЀ <4BdBdK*0Lz___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p ___PPT9|t ?LNov 9th 2006 Jan 5th 2005O =&?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?tOPPPP+PO+s -6What interactions generate greatest student engagement77(6 XAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages (asking questions) generated significantly more (24) reads pre message than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersfYP]"X &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Correlation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsPeer Facilitation does work Students quickly identify valuable contributors Early stages crucial Changing Contributor to Facilitator Identification of thought leaders Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /P%&'(*+,./ 0 1 T  0 kc@T(  Tx T c $d@   t T C LA4CommunityofInquiry-better` T 6@x aGarrison et al 2000 H T 0޽h ? ̙33___PPT10i. @'+D=' d= @B +  0 2(  r  S B`  B t  C LA4CommunityofInquiry-better` R  C *Acyclical`X  C 0Astahl-model` P  0d0 `*  < Stahl 2006 2   0ld0 0*  FMuukkonen et al 1999 2H  0޽h ? ̙33___PPT10i.=+D=' d= @B +e0  u(  X  C <   H  S `H< @  H wcCommunity members move between internal reflection and external debate. Iterative cyclical process.H  0޽h ? ̙3380___PPT10.=h0 0x(  X  C <   d  S d< @  d zLOther cyclical models of inquiry and knowledge building. Muukkonen and StahlGH  0޽h ? ̙3380___PPT10.0r$g!-C%0 )C,C.11x0( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  @@`` 6J)     BS  !"#$'()*+,-./ 0123`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0jppp@ <4!d!d))0LЀ<4dddd))0LЀ <4BdBdK*0Lz___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p ___PPT9|t ?LNov 9th 2006 Jan 5th 2005O =&?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?tOPPPP+PO+s -6What interactions generate greatest student engagement77(6 XAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages (asking questions) generated significantly more (24) reads pre message than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersfYP]"X &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Correlation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsPeer Facilitation does work Students quickly identify valuable contributors Early stages crucial Changing Contributor to Facilitator Identification of thought leaders Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /P%&'(*+,./ 0 1 r/._11x0( / 0DTimes New RomanLLԖ-a0ԖDArialNew RomanLLԖ-a0Ԗ DWingdingsRomanLLԖ-a0Ԗ@ .  @n?" dd@  @@`` 6J)     BS  !"#$'()*+,-./ 0123`b$\{>rL'U^b$BČdAuV]b(#TC^b$]LKߞqֈv&b$GOw[pŚsLb$oޅM&3qS[b$tPᎂ*2sK OqZBb$٠afT59$yb$]ׯr)aNpZ 0AA@ʚ;Q,ʚ;g45d5d-a0jppp@ <4!d!d))0LЀ<4dddd))0LЀ <4BdBdK*0Lz___PPT10DTimes New RomanLLp-a0pDArialNew RomanLLp-a0p ___PPT9|t ?LNov 9th 2006 Jan 5th 2005O =&?Determinants of Engagement in an Online Community of Inquiry  @> ? rJim Waters College of Information Science and Technology Drexel University Philadelphia james.waters@drexel.edu ss$Z>0[q BackgroundProblem of maintaining student engagement. Online learning creates separation Alienation, lack of commitment and antisocial behavior ? Community of Inquiry ?$$ 9Pragmatism: Dewey and Addams Problematic situation, scientific attitude and community as participatory democracy Inquiry is controlled or directed transformation of an indeterminate situation There is a community engaged in inquiry. Inquiry is an open-ended process with positive feedback. Dewey (1916,1933) n" PCommunity of Inquiry   Cycles of Inquiry ( )$Building on the Garrison et al Model%%(Content Analysis of online Discussion Board Graduate Information Systems Students Open-ended debate Practical and Theoretical questions Derived behaviors that incorporated different elements of the Garrison model   Student RolesResearch QuestionsAre there noticeable patterns of interactions between participant roles? Do patterns of interaction change over time? Does the online learning environment support critical inquiry ? What interactions generate greatest student engagement "  Study  Raw results  Student behaviorContributor (61%) Facilitator (22%) Fluid patterns of class behavior Students adopt different behaviors from week to week Popularity and volume were unrelated Possible connection between facilitation and popularity/reference to poster..0Z2MDetailed Analysis(gNine typical threads analysed Three threads each for weeks 3, 6 and 9 The most productive debate produced 30 messages with a maximum thread depth of 7. The least productive produced 14 messages with a thread depth of 2. The mean number of messages on a discussion was 22 Four discussions had a thread depth of greater than 3. Pattern of responses analysed hZhg JAre there noticeable patterns of interactions between participant roles? KKJ ,Do patterns of interaction change over time?--,  -?Does the online learning environment support critical inquiry ?@@ ?  ?Does the online learning environment support critical inquiry ?@@? gFew threads reached a definitive conclusion Closer synthesizes and ends debate Closer often ignored Elements found Information Gathering Synthesis Concrete experience Reflective observation. Critical evaluation Deepening questions Generating subordinate questions Refining given knowledge Generating hypotheses Open-ended debate ? Not problem centered ?tOPPPP+PO+s -6What interactions generate greatest student engagement77(6 XAnalysis of all 951 student messages Analysis of Read frequency for different message types Knowledge-elicitation messages (asking questions) generated significantly more (24) reads pre message than any other type of message. Average reads per message for all messages is 16.78 Some participants messages are read more frequently than othersfYP]"X &Who are the most attended to posters ?''( $Why are some posters more engaging ?%%(Does frequency of posting messages affect popularity? Does length of message affect frequency of reads? Does position of messages affect frequency of reads ? Does type of  participant affect frequency of reads ?"i m  0Is frequency of posting related to popularity? 11$0 Correlation between number of messages and total reads of a persons messages is 0.97, Weak -0.21 correlation between frequency of posting and reads/message. Most frequent poster posted 136 messages which attracted an average of 15.65 reads per message. The average messages per person was 37 Top three most attended to participants posted an above average number but subject 20 did not. Two of the least attended to participants posted well above average numbers of messages.Z !/Does length of message relate to read frequency00(pCorrelation between length of post and reads for that post = 0.011 Grouping messages into very short (< 101 words), Short (101 200 words), medium (210 300 words) and long (>301 words) One-Way ANOVA on frequency of reads gives an f value of .373 and a significance level of .773, no apparent significant effect9Z98 "2Does position of message affect frequency of reads33(*Messages posted in the first 2 days of a thread are read significantly more frequently (f=36.339, p= 0.000) than later messages. Messages posted after the third day are read by less than 50% of participants. If a message is one of the first 10 posted it is much more likely to be read than later messages (f=22.564, p = 0.000). However only two of the most attended to participants are  early posters.BP  #2Does type of participant affect frequency of reads33(The most attended to participants posted more facilitation messages (39% of messages posted) The least attended to participants typically posted far fewer facilitation messages. (23% of messages posted).6MZ   ConclusionsPeer Facilitation does work Students quickly identify valuable contributors Early stages crucial Changing Contributor to Facilitator Identification of thought leaders Asking questions gets responses Fluid patterns of behavior within the community Volume is not the same as quality  Future Work  :Small, exploratory study Initial framework Open to debate *;Z:  Questions? ` /P%&'(*+,./ 0 1 r__711