00:00 Welcome everybody.
00:01 It's really a pleasure to
00:04 say hi to all of you to this World Development Report 2024 seminar,
00:11 which is focusing on higher education for social mobility and talent development,
00:17 in particular in the case of Chile.
00:20 As you know,
00:21 the upcoming world development report that is going to be
00:25 published,
00:25 uh,
00:26 very soon,
00:26 hopefully
00:27 in a few months
00:28 is going to be focusing in particular on a very relevant issue
00:33 for the World Bank and I think for many of us,
00:36 uh,
00:36 in the developing community
00:38 which is economic growth in middle income countries
00:42 and within this research that is being conducted by.
00:45 Really
00:46 excellent team of experts and academics and development practitioners
00:51 from the World Bank and also with the support
00:53 wither colleagues and thinkers from from around the world
00:57 one issue that came of course to be absolutely relevant
01:02 when thinking about economic development and
01:04 economic growth in middle income countries,
01:07 it is the the role and the importance of education.
01:11 And in particular of higher education and,
01:15 and of investing in higher education and investing of course in,
01:19 in human capital.
01:21 So this seminar today within this framework wants to really
01:25 take a deeper dive
01:27 on what has happened and,
01:28 and in particular on,
01:29 on some innovative results and,
01:31 and research
01:33 that has been taking place for the case of Chile.
01:36 I am Cecilia Naam.
01:37 I'm the executive director representing at the board of
01:41 the World Bank 6 countries from the southern cone,
01:44 including,
01:44 of course,
01:45 Chile,
01:46 so it's really a pleasure to be here
01:49 with you today.
01:50 In,
01:50 in our chair,
01:52 in our countries.
01:53 We give
01:54 an absolutely central role to investing in
01:58 education and to investing in particular in,
02:00 in higher education.
02:02 In fact,
02:02 not only higher education,
02:04 I must say that we care
02:05 significantly about investing in science,
02:08 in technology,
02:09 in research.
02:10 I am from Argentina,
02:12 so in the case of,
02:13 of Argentina.
02:14 We have a significant part of our
02:16 national budget that not only goes to education,
02:19 you know,
02:19 but also
02:20 to investing in science and technology and integrating
02:24 the scientific
02:25 and the academic,
02:26 uh,
02:26 sides of the
02:28 RMT
02:29 and we really believe that this is an absolutely
02:32 essential component of creating and sustaining economic growth,
02:36 uh,
02:36 over time.
02:37 The,
02:37 the investment
02:39 in human capital
02:41 not only can can can significantly impact.
02:44 Future productivity and the life-life er incomes of the children and youth,
02:50 but of course,
02:51 it's also
02:52 er
02:53 key
02:54 for sustaining economic growth over time and for boosting innovation er over the,
03:00 the medium term.
03:01 There's also a very important component that I like to highlight when we discuss
03:07 education and when we think
03:09 about investing in our people and investing in,
03:12 in our youth.
03:13 Which is that there's another uh a
03:16 specific sustainable development goal that is also related
03:21 with education you know that the World Bank
03:23 has recently enhanced
03:26 uh our mission and our vision as an institution
03:29 and we are providing uh an even bigger
03:32 role to the connection between development challenges that the
03:36 World Bank focuses in and the sustainable development.
03:38 Development and goals.
03:39 So I think it's also worth
03:41 reminding us today that SDG 4
03:45 calls us,
03:46 all of us,
03:46 all countries around the world have committed to the SDGs
03:50 to ensure inclusive and equitable quality
03:54 education
03:55 and to promote
03:56 lifelong learning opportunities
03:59 for all.
04:00 And this is exactly the,
04:01 the framework in which I also think
04:04 we need to.
04:06 Appro our conversation.
04:08 Uh,
04:08 there's recent.
04:12 Economic
04:13 Commission from Latin America and the Caribbean ECLAC
04:16 that shows that in the course of the last two decades
04:19 our region LC
04:21 has seen an extraordinary increase in terms of the access to higher education.
04:26 It shows that if we take uh almost a 20 year span from the 2000 to 2018,
04:32 the gross enrollment rate has increased from 19%
04:36 to around 38%.
04:38 Uh,
04:38 this is something that we cherish and that we celebrate because we,
04:42 again,
04:43 strongly believe that investing and supporting our young people,
04:46 our children.
04:47 To get more
04:49 access to education is absolutely
04:51 important.
04:52 Of course,
04:53 significant challenges remain.
04:55 This study and other studies
04:57 also showed that we still have a significant
05:00 uh work to do to ensure equal opportunities not only
05:04 for access but also for the retention and for the completion
05:07 of the education cycle.
05:09 including at the higher level of education
05:12 so I think that the discussion that we're going to have today
05:15 can be really helpful to to approach these issues
05:18 and to rethink once again
05:20 what is the specific role,
05:22 you know,
05:23 of education and investing in higher education
05:26 uh for a development strategy
05:31 uh I would like to ask our
05:33 panel uh colleagues to.
05:35 To take the floor today we will first
05:38 hear
05:39 a very interesting presentation,
05:41 uh,
05:42 that of course again is focused on the case of
05:44 Chile that has a lot of significant lessons to,
05:47 to share with all of us.
05:49 So the first,
05:49 uh,
05:50 speaker is going to be Sebastian Nachegos.
05:53 I'm gonna introduce Sebastian now.
05:55 Following Sebastian,
05:56 we will also listen,
05:58 uh,
05:58 from research from Ricardo Paredes.
06:01 I will introduce you,
06:02 Ricardo,
06:03 a bit later.
06:04 But Sebastian
06:06 is going to,
06:07 to talk with us today.
06:09 He's er an economist er who comes from the Hawaii Business School and he's also a
06:16 member of the Human Capital and Economic Opportunity
06:19 Global Working Group at the University of Chicago.
06:23 And he will be presenting today,
06:25 in particular his paper
06:27 on
06:27 50 years of college entrance,
06:30 entrance exams
06:32 and gaps in access to college in Chile.
06:36 This is a paper that is co-authored
06:38 with uh Andres Barrio Fernandez and also with Christopher Nielsen.
06:43 So please,
06:44 uh,
06:45 Sebastian,
06:45 it's nice to welcome you to this uh seminar series
06:49 and please uh feel free to take the floor.
06:54 Thanks a lot for that nice introduction,
06:57 Cecilia and for introducing us to this topic.
06:59 I'm super passionate about this.
07:01 Um,
07:02 let me,
07:03 let me share my,
07:04 my slides with you guys,
07:05 um.
07:09 Works.
07:14 All right.
07:15 Seems like we're on.
07:18 Can you see this?
07:23 We see you,
07:23 Sebastian.
07:24 All right.
07:25 All right.
07:25 So,
07:25 so thanks a lot.
07:26 I,
07:26 I also wanna,
07:28 wanna thank the,
07:29 uh,
07:29 the team at the World Bank led by Maria Marta Ferreira,
07:32 uh,
07:34 for the invitation and for many discussions that we have had here.
07:38 Also thanks to the rest of the team,
07:40 Joyce,
07:40 uh,
07:40 and,
07:40 and so on.
07:41 I,
07:41 it has been like a,
07:42 a pleasure to,
07:44 uh,
07:44 to do this.
07:45 Um,
07:46 also very happy to,
07:47 to share the floor with Ricardo.
07:49 He's a renowned.
07:50 Uh,
07:51 colleague,
07:51 I'm super happy to,
07:52 nice to see you,
07:53 Ricardo.
07:54 So,
07:54 yeah,
07:54 I'm,
07:55 I'm just,
07:55 I'm just gonna start,
07:57 uh,
07:57 I'm already introduced my co-authors too.
08:00 Uh,
08:00 I just wanna say that this is,
08:02 this is work in progress,
08:03 all right.
08:04 Uh,
08:04 so we are,
08:06 we are trying to make sense of a lot of data,
08:08 but,
08:09 um,
08:10 let me
08:11 give you like a super short summary so that you guys know that you're like
08:16 Uh,
08:17 with
08:18 whole super focused,
08:19 now,
08:20 I'm gonna try to give you the beef like
08:22 uh at,
08:22 at the very beginning.
08:23 So
08:24 what
08:25 are we doing in this paper?
08:27 What?
08:27 Uh,
08:28 is the,
08:28 the main
08:30 reason that we are pursuing this research
08:32 is that we care about the fundamental question.
08:35 So we care about how countries develop.
08:37 So this is sort of
08:38 like a big question behind our,
08:40 our research
08:41 and to answer this question,
08:43 of course it's a big one,
08:44 we typically don't have like long series of microdata to
08:49 document what's going on with development across groups,
08:52 space,
08:53 and over time.
08:54 Um,
08:55 so we.
08:57 In this paper,
08:59 we
08:59 try to fill this gap a little bit
09:02 uh uh about the evolution of long-run
09:06 opportunities and let me put this like it's opportunities defined in
09:09 a way that I'm gonna talk uh tell you about later
09:13 um.
09:14 So this,
09:14 we described the evolution of
09:17 educational opportunities over the last 5 decades with microdata
09:21 for a particular country in,
09:24 uh,
09:24 in Latin America which is perhaps
09:27 the fastest growing country in the region and
09:30 we believe that this
09:32 following the,
09:32 the words by,
09:33 by you,
09:33 Cecilia,
09:34 this could probably,
09:35 uh,
09:36 show us,
09:37 give us some insights on how,
09:40 uh,
09:41 what can we learn from
09:42 the development process.
09:44 Um,
09:45 so this is just to,
09:46 to motivate,
09:47 this is,
09:47 uh,
09:48 a graph showing,
09:49 uh,
09:51 the enrollment in higher education as a percentage and,
09:54 uh,
09:55 economic growth as measured by low GDP per capita.
09:58 And so this,
09:59 this tip of,
10:01 uh,
10:02 The data points for,
10:03 for,
10:04 for Chile really like our
10:06 uh quick.
10:08 Um,
10:08 uh,
10:09 economic growth uh in the,
10:10 in the 90s basically.
10:12 Uh but then like the higher levels of,
10:16 of education enrollment that we have reached
10:18 put us
10:19 like in between the United States and India in terms of the
10:23 uh
10:24 uh and the
10:26 Economic growth,
10:28 but then like super high in terms of development,
10:30 even,
10:31 even in,
10:31 in terms of
10:32 uh enrollment in higher education,
10:33 even higher than the US
10:35 and well,
10:36 well,
10:37 well above India.
10:38 Uh so this is where like Chile stands
10:41 and so what,
10:41 what do we do?
10:42 We put together a unique data set from Chile using this
10:47 uh
10:48 Tests
10:50 that Chile uses to uh for admission in higher education
10:53 and we do this with uh using
10:57 test takers from 1967 onwards.
11:01 We digitize the historical records in paper.
11:03 It was exhausting,
11:04 but we did it
11:05 and we combined it with modern
11:08 data sources and then we are,
11:10 we are now merging this data with available
11:13 uh records from.
11:15 Uh,
11:15 from administrative processes,
11:17 uh,
11:18 like enrollment,
11:19 graduation,
11:20 teachers censuses,
11:20 and more.
11:21 And if you,
11:22 if you,
11:22 what else,
11:23 I mean,
11:23 if you have ideas,
11:24 we welcome them,
11:24 uh,
11:25 and I think that we,
11:26 we could do a lot,
11:27 a lot,
11:28 uh,
11:28 more than,
11:29 than what,
11:30 what we are gonna,
11:31 uh,
11:31 see today.
11:33 Uh,
11:33 what do we find?
11:34 We find
11:36 4 novel results.
11:37 It was tough to pick,
11:39 to pick them because there is a lot going on.
11:41 But let's,
11:42 let,
11:42 let me say that the gender gap in scores
11:45 dropped by a factor of 10.
11:47 So this is in,
11:48 uh,
11:48 between 1967 and,
11:51 and 2017.
11:53 So this is basically saying,
11:55 hey,
11:55 uh,
11:56 boys
11:57 had uh,
11:57 uh,
11:58 like a 0.5 standard deviations above women uh
12:02 at the beginning and then towards the end,
12:04 that's
12:05 Close to zero,
12:07 OK.
12:08 The ethnic gap measured by the fraction of,
12:10 of Mapuche people,
12:12 which is the biggest ethnic group living in Chile,
12:15 has dropped by about half in both scores and participation in the exam.
12:21 The share of uh lower socioeconomic status,
12:25 uh,
12:26 test takers
12:26 taking the exam
12:28 has increased by a factor of 1.5.
12:30 And in terms of geography,
12:32 we find an,
12:33 an increasing the take-up for underrepresented areas of,
12:37 of about 10%.
12:39 Um,
12:39 so I think that and this is,
12:41 these are good news in general.
12:43 Um,
12:43 we think that we are uncovering some important long term progress on a host of,
12:48 on a host of metrics
12:50 that typically,
12:51 uh,
12:52 it's,
12:52 it's hidden
12:53 in the,
12:53 in,
12:54 in the data,
12:54 in the short term data.
12:56 So imagine that we have something like this and we are,
12:58 we are,
12:58 we are like over here and then,
12:59 oh no,
13:00 something bad happened like a pandemic,
13:02 and then we say,
13:02 oh no,
13:03 we are super,
13:04 this is,
13:04 this is the worst.
13:05 How can we even recover?
13:07 But then like we're
13:08 Saying look,
13:08 all right,
13:09 but you're,
13:10 I mean,
13:10 you're there
13:12 and uh this is just
13:13 probably it could help us to,
13:15 to,
13:15 to have a more nuanced view
13:18 about the development process.
13:19 Uh of course,
13:20 short term results matter a lot,
13:22 but uh,
13:23 but we think that we are,
13:24 we are providing some
13:26 uh evidence on,
13:27 on,
13:28 on,
13:28 on that long term process.
13:30 Despite the progress,
13:31 of course,
13:31 there are many challenges ahead.
13:33 I mean,
13:34 uh,
13:34 we have these uh increases in
13:37 In,
13:37 in take up,
13:38 but
13:39 if you,
13:40 if we take a look at the what's going on at the very top of the distribution,
13:44 we're still missing,
13:45 uh,
13:46 more women at the top of the distribution of,
13:48 of scores,
13:49 uh,
13:50 we're missing more
13:51 um
13:52 individuals from low socioeconomic status at the very top and so on.
13:57 So there,
13:58 there,
13:58 there is a lot to
13:59 this,
14:00 the thing is not solved,
14:01 it's far from solved,
14:03 but the thing that,
14:04 that,
14:04 uh,
14:04 um.
14:05 It's important to see like the big picture thing here
14:09 and
14:10 And I think that we,
14:11 we are providing some insights in how,
14:14 how is it that,
14:15 that,
14:15 that countries developed,
14:16 but this is from a very humble,
14:18 uh,
14:18 point of view.
14:18 I think that there's a lot more to do and uh a lot more to do,
14:23 uh,
14:23 beyond descriptives,
14:24 but we are still,
14:25 I'm just gonna show you some descriptives today,
14:28 not anything that,
14:29 that's trying to be causal.
14:31 Um.
14:33 I'm gonna go a bit
14:35 fast on the construction of the data set,
14:37 but if he wanted to show you this because this
14:39 was not something that we sort of downloaded from,
14:42 from somewhere to just run analysis.
14:45 Just
14:45 from a bit of a context,
14:47 the mission system to higher education in Chile.
14:50 Uh,
14:50 has,
14:51 uh,
14:51 an,
14:51 an SAT equivalent
14:53 called
14:54 the Prueva Aptitude Academica,
14:57 uh,
14:57 which ran from 1967 until 2003,
15:01 and then in that year
15:02 we have another one called TSU that ran until 2020
15:06 and then we
15:07 creative and then now we have other names.
15:08 Now it's called PI,
15:10 right?
15:10 But,
15:11 anyway,
15:12 so basically people take the test
15:14 and then they,
15:15 they apply with the scores in hand and their uh GPA from high school
15:20 to uh career and college combinations.
15:23 Uh,
15:24 and the,
15:24 the,
15:25 the process is,
15:26 it resembles a deferred acceptance algorithm
15:29 uh where basically everyone is um
15:32 providing their
15:34 applications and then the schools and majors decide how to allocate the seats
15:38 based on these scores and their,
15:40 and their GPA and the preferences of the students.
15:44 Um,
15:45 so this system has remained more or less,
15:49 more or less,
15:50 um,
15:52 Without changes since 1967,
15:56 there have been some,
15:57 some changes but the absence of the
15:59 uh of the
16:01 Of the mission process is the same.
16:04 And so this here you can take a look at one
16:08 process that was in 1977.
16:11 OK,
16:11 I,
16:11 I was not even born,
16:13 uh,
16:13 so,
16:13 but this is like,
16:14 I mean they,
16:14 they have everything,
16:16 all this,
16:16 all the,
16:17 the,
16:17 the results if uh uh
16:19 uh were like posted like this with the name of the applicants,
16:23 the whole name,
16:24 IDs,
16:25 the scores,
16:25 and so on,
16:26 and this is just one.
16:27 There are many other.
16:28 Books.
16:29 Like there were many books and we,
16:31 we went there to the basements of the agency that's in charge of this
16:36 and we were like,
16:37 I,
16:38 I like to say that we were the actual researchers like Indiana
16:41 Jones where you go and you open these books and there's a,
16:44 they're covered with dust.
16:46 Uh,
16:47 and you generate evidence from that anyway,
16:49 so what,
16:50 what we did,
16:50 we collected the digital copies of the old books,
16:53 we send the images to India to be pre-processed,
16:55 then we had this exhaustive back and forth auditing the process
16:58 data and we supplemented that with aggregated information from official reports.
17:03 So we basically had like 24 million test scores,
17:07 um.
17:08 Digitized 6.5 million observations
17:12 and well,
17:12 the,
17:12 I,
17:13 I mean,
17:13 it,
17:13 it's a lot of information,
17:14 more than 400 books and so on.
17:17 So this is just to tell you,
17:18 oh,
17:19 this is with uh an important effort
17:22 uh uh and anyway,
17:23 it's just,
17:23 it has taken us many,
17:25 many years so I'm very happy to share this with you.
17:28 Today.
17:28 I'm not gonna share more,
17:29 more details about the books and stuff like that,
17:32 um,
17:32 but,
17:33 uh,
17:33 but I,
17:33 you say I wanna
17:34 go and show you some,
17:35 some data.
17:36 The last thing I want to show you regarding the construction of the data
17:39 is that even though we didn't have
17:42 like the micro data because that's what we did.
17:43 We recovered that data basically,
17:45 they were all aggregated data sources.
17:48 So there was,
17:48 there was one book in 1985
17:50 which said in 1967 there
17:53 2,
17:54 29,000 people taking the exam,
17:57 more or less.
17:58 So what we did is that we,
17:59 uh,
18:00 well,
18:01 here we have the data from these external aggregated sources
18:05 and then I'm gonna show you how we did
18:08 and this we didn't know how
18:10 this is gonna go,
18:11 uh,
18:12 and basically that's,
18:13 that's our data.
18:13 These are counts of test takers per
18:16 uh per year.
18:17 Uh,
18:18 and,
18:18 well,
18:18 here it's easier to see how we did,
18:20 so this is like,
18:22 it was like,
18:23 uh,
18:24 super excited when I,
18:25 when I,
18:25 when I saw this,
18:26 uh,
18:26 so it's basically we,
18:27 we,
18:28 we could
18:29 replicate
18:30 almost,
18:30 uh,
18:31 the exact amount of,
18:32 uh,
18:32 test takers that were,
18:34 um,
18:35 uh,
18:36 indicated in the
18:37 aggregated data books.
18:39 So that,
18:40 that,
18:40 that was,
18:41 that was great.
18:42 Uh we have more,
18:43 we have,
18:43 we have uh um test scores
18:45 uh in,
18:46 in,
18:46 in
18:47 subjects biology,
18:48 chemistry,
18:49 physics,
18:50 social sciences.
18:50 We have a lot more.
18:51 I'm not gonna do anything with,
18:53 with this today,
18:54 uh,
18:54 but,
18:55 but yeah,
18:55 things,
18:56 things were pretty,
18:57 pretty good
18:57 up until 2003
18:59 and this is how,
19:01 this is,
19:01 this is the count
19:02 of
19:03 the test takers
19:05 per year.
19:06 Here we have a year and here we have the count.
19:09 Uh,
19:10 in the last 50 years.
19:11 OK,
19:12 so we have increased from about like 30,000
19:16 people taking the exam to about
19:18 10 times that,
19:19 3000,
19:20 300,000 people.
19:21 Now,
19:22 you could say,
19:22 hey,
19:23 but Ceba that is like because like the population of Chile has grown.
19:26 Yes,
19:27 but we haven't,
19:28 and the population has not
19:30 grown at the rate of 10
19:32 times.
19:33 It,
19:33 it was uh uh the rate is like 5 times I think or more,
19:36 more or less that so we were like
19:38 3 million or so in,
19:40 in the,
19:40 in the,
19:40 in the sixties and now we are
19:42 17,
19:43 probably more.
19:44 Let's say 20 million.
19:45 That's 5 times,
19:46 it's not 10 times so
19:48 I think we have done like uh important progress in like
19:53 opportunities measured us this idea,
19:57 number of people that is taking the exam to access higher education.
20:02 All right.
20:02 Um,
20:03 so let me show you some results regarding gender.
20:06 This is,
20:07 this is just the number,
20:08 the raw number of women taking the college entrance exams.
20:11 So it,
20:11 it has raised by,
20:13 I don't know,
20:13 like they were like 10,000,
20:15 in 1967 to 100,000
20:19 later on.
20:19 This is just the count,
20:20 but again,
20:21 the fraction of women has not increased by 10,
20:23 by the,
20:24 by a rate of 10.
20:25 Uh,
20:26 and then this is
20:27 like the fraction of women eligible for elite college and majors.
20:31 Elite colleges and majors are,
20:34 um,
20:35 the,
20:36 uh,
20:36 majors of
20:37 business,
20:38 medicine,
20:39 engineering,
20:40 um,
20:41 and law at the,
20:43 at the two,
20:45 top universities in Chile,
20:46 uh,
20:47 University of Chile andia Catholic according to test scores.
20:50 And so it has increased by,
20:51 by a lot,
20:52 importantly,
20:53 5 times.
20:54 Uh,
20:55 the gender gap
20:56 in,
20:57 in,
20:57 in math,
20:59 in math and reading,
21:00 so this is math,
21:01 has decreased a lot,
21:03 uh,
21:04 and,
21:05 but there's still a gap now,
21:08 but then if you,
21:08 well,
21:08 if you take a look at the gender in,
21:10 in the gender gap in reading,
21:11 it has declined from 0.4 standard deviations to basically 0 now.
21:16 See,
21:17 uh,
21:17 this is,
21:18 uh,
21:18 pretty,
21:18 pretty impressive,
21:19 uh,
21:20 and now we,
21:20 we can take also look at what what's going on,
21:22 not on average but the details of the distribution
21:25 and um I would say that the most
21:28 interesting thing
21:30 is that at,
21:30 at least in terms of language,
21:33 we have uh girls
21:36 reaching
21:37 the 50% which is like
21:39 what we would like to have more or less,
21:40 you know,
21:41 like half of the
21:42 uh
21:43 Of the girls that are at the top 5%,
21:47 uh,
21:48 and 5 of them,
21:48 half of them are girls and the other half are,
21:50 are men.
21:50 In,
21:51 in language,
21:51 they're still
21:52 uh below,
21:53 uh,
21:54 behind,
21:54 I would say in,
21:55 in,
21:55 in math.
21:56 Uh,
21:57 the girls at the bottom
21:59 of the distribution,
21:59 we also,
22:00 I mean,
22:00 it's,
22:01 it's more.
22:02 Tends to be similar in,
22:04 in,
22:04 in terms of uh
22:06 uh math and,
22:07 and,
22:07 and language still,
22:08 still there,
22:09 there are a bit more
22:10 uh
22:12 a fraction of of women in there.
22:14 So
22:15 there,
22:15 there are still things to do.
22:16 I mean this is just to say,
22:18 look at this huge improvement.
22:20 Really,
22:20 really huge.
22:21 Maybe some other countries also have experienced this growth,
22:25 uh,
22:25 in,
22:25 or this decrease in the gender gap in scores,
22:28 but we don't know.
22:30 So now 11 thing that we have here is to say,
22:32 hey,
22:32 we have the data,
22:34 uh,
22:34 and we can show what,
22:35 what
22:36 has happened over 50 years of time.
22:38 Um,
22:39 so.
22:41 In terms of
22:43 ethnicity and low socioeconomic status,
22:45 um,
22:46 the Mapuche descendants
22:49 have
22:50 increased by 4 the number of those who are select
22:54 who are eligible for for these elite degrees.
22:58 Uh,
22:59 and then,
23:00 the,
23:00 the,
23:01 the fraction of
23:02 low,
23:03 the number of low socioeconomic status students eligible
23:06 for these elite,
23:07 uh,
23:09 degrees has also risen by 4.
23:12 So I,
23:12 I don't know,
23:12 like you guys could say,
23:13 OK,
23:14 so,
23:14 but that's because the base was super low,
23:17 yeah,
23:18 the base was super low,
23:19 basically nobody was,
23:20 was getting in there before like 50 years ago,
23:23 but still,
23:24 I mean,
23:24 there is a steep.
23:25 Increase in the,
23:26 in,
23:26 in the last years and,
23:27 and I think that there,
23:28 there's something
23:29 positive going on in here.
23:32 Um
23:33 And then we,
23:34 we,
23:34 we can do more like,
23:35 let,
23:35 let's take a look at the share in the top 5% by ethnicity
23:39 and uh in,
23:40 in
23:41 starting in,
23:41 in,
23:41 in the,
23:42 in the 70s,
23:43 well,
23:43 there was basically nobody there.
23:45 Uh
23:46 And now that,
23:47 I mean,
23:48 that,
23:48 that has increased importantly and we,
23:50 we have some of them
23:52 at the very top.
23:53 Um we have,
23:54 we are doing more so this is like,
23:56 let's take a look at,
23:57 at another dimension like
23:59 geography and let's take a look at,
24:00 at municipality,
24:02 students from municipalities with low levels of schooling in the 80s
24:05 and we again see that the number of those who are
24:09 Being eligible for uh selective care uh the selective degrees is,
24:13 is increasing.
24:15 Same thing for low socioeconomic status students.
24:18 So,
24:19 um,
24:20 I have a couple of graphs sharing uh uh summarizing what's going on,
24:25 uh,
24:25 and I'm
24:26 finishing up here.
24:28 Uh,
24:29 let me,
24:30 let me,
24:30 let me finish with,
24:31 with,
24:32 with this one which is
24:35 The graphs are showing us
24:36 changes.
24:37 These are changes,
24:38 right?
24:39 Changes in the number of students eligible for selective
24:43 careers or elite degrees and the share of students,
24:46 the change in the share of students selected for,
24:49 selected for this,
24:50 uh,
24:51 uh,
24:51 eligible for these degrees.
24:53 And basically,
24:54 we,
24:54 I mean,
24:54 female students have increased.
24:57 Both in number and in share,
24:59 low socioeconomic status in number and in share
25:02 for Mapuche descendants,
25:03 it's,
25:03 they have increased
25:05 uh comparatively less,
25:06 uh,
25:07 but still,
25:07 I mean,
25:08 this is like,
25:09 uh,
25:10 these,
25:10 these are important increases and basically the,
25:12 the,
25:13 the guys,
25:14 the students that can
25:16 That are eligible for the elite degrees,
25:17 they're basically,
25:18 this is a,
25:19 a life changer,
25:20 right?
25:20 At least in Chile,
25:22 if you go to one of these
25:24 majors,
25:25 medicine,
25:25 business,
25:27 engineering,
25:28 uh,
25:28 law at University of Catolica or University of Chile,
25:31 basically,
25:31 I mean,
25:32 you're at the very top of the distribution of
25:34 Uh,
25:35 of income in,
25:36 in,
25:36 in the country.
25:37 So,
25:37 uh,
25:37 these are like very important,
25:39 uh,
25:39 uh,
25:39 this is very important progress
25:41 and I'm just
25:42 gonna
25:43 end up with the same slide that I showed you at the beginning
25:47 so that at the beginning,
25:48 if you were,
25:49 uh,
25:50 focused at the beginning,
25:51 that was it.
25:52 I'm not sharing anything,
25:54 uh,
25:54 additional
25:55 to,
25:55 to that slide,
25:56 but now probably,
25:57 I mean,
25:57 you took a look at the data and probably you're,
26:00 hopefully you're excited and full of ideas to what of,
26:02 uh.
26:03 What to do with this.
26:04 So I'm very happy to,
26:06 to hear your thoughts and,
26:07 and comments.
26:08 Thanks a lot.
26:12 Mm,
26:13 well,
26:13 thank you.
26:14 Thank you,
26:14 Sebastian.
26:15 I think that the data is very relevant
26:18 uh for the,
26:19 for the debate and the reflections that we're having,
26:21 of course,
26:22 the issue of equality in access
26:25 is absolutely fundamental,
26:26 so,
26:26 so the,
26:27 the data,
26:28 the information can really
26:30 be a,
26:30 a good input,
26:31 right?
26:31 For,
26:32 for the bigger conversation in terms of the,
26:34 the design of higher education and,
26:36 and public policies uh in terms of higher education,
26:39 you know,
26:39 in the case of Argentina.
26:41 We are very proud of a very strong public education system with free access
26:46 uh for students,
26:47 so it's,
26:48 it's a different uh design,
26:50 a different approach,
26:51 but many of the,
26:53 of the discussion that I think we're having can really be.
26:56 Be strengthened by,
26:57 by this uh conversation.
26:59 Uh,
26:59 in particular,
27:00 I think the key question is,
27:01 as I was mentioning before,
27:03 right?
27:04 Uh,
27:04 how can we ensure a system of education,
27:07 of higher education can be a key to upward social mobility and,
27:11 and for social integration.
27:13 Uh,
27:13 and for development
27:15 in,
27:15 in a sustainable way.
27:16 And I think the other paper that we are
27:19 going to be listening from today can,
27:21 can also be a,
27:22 a good input for that reflection.
27:24 This is a,
27:25 a document that is going to be presented by Ricardo Paredes.
27:29 Welcome,
27:30 Ricardo as well.
27:31 Uh,
27:32 Ricardo is currently
27:34 a minister of the Tribunal de la Libre Compettencia in Chile,
27:38 and he's going to present,
27:39 uh,
27:40 a paper that I think complements the previous one.
27:43 Which is uh a document uh called DOC
27:47 and the Higher Vocational Technical Education in Chile,
27:51 uh,
27:52 which is certainly,
27:53 uh,
27:53 also I think relevant for,
27:55 for the bigger discussion about development
27:57 and the role of uh
28:00 education and human capital in that.
28:02 So,
28:02 please,
28:03 uh,
28:03 Ricardo,
28:04 go ahead and,
28:05 and welcome to this conversation.
28:08 Thank you very much,
28:09 Cecilia and Maria Marta and the staff and
28:12 hello to everybody,
28:14 especially
28:15 Sebastian.
28:17 Um
28:18 let me
28:19 See how can I share this is uh there's something,
28:23 uh,
28:24 yeah,
28:24 yeah.
28:27 Yeah.
28:33 I am sharing
28:35 the,
28:36 the presentation or
28:38 you see the whole thing or
28:40 just a part of?
28:43 There
28:46 OK.
28:48 That's better,
28:49 yeah.
28:51 OK,
28:51 should I
28:54 There
28:56 Oh,
28:56 I wanna see,
28:57 I wanna see Ricardo.
28:59 Super.
29:00 Thank you again.
29:01 OK,
29:01 so let me
29:08 Or
29:09 Mm
29:13 OK.
29:14 OK.
29:15 So the,
29:16 the history of technical and vocational education in Chile is shared with uh
29:21 many Latin American countries
29:23 is uh basically the same.
29:26 In,
29:26 in the very beginning,
29:27 er in the colonial times,
29:30 basically,
29:30 it was conceived.
29:33 By the
29:34 religious orders,
29:36 uh,
29:36 priests and the Catholic Church basically
29:40 to help unskilled or illiterate,
29:42 illiterate,
29:43 uh,
29:44 uh.
29:46 Persons.
29:47 That's,
29:47 that's basically and,
29:50 and uh
29:51 that,
29:52 that was very informal.
29:55 Uh,
29:56 and,
29:56 uh,
29:57 then in the middle of,
29:59 of the 19th
30:01 century,
30:02 uh,
30:02 there was a discussion and an intellectual discussion
30:06 that separated basically when become,
30:09 became formal,
30:10 this kind of education,
30:12 the,
30:12 the,
30:13 the government put money there.
30:15 uh
30:16 uh the discussion
30:18 uh was basically
30:20 The humanities
30:23 for the selected uh
30:25 uh for a selected group,
30:27 group of people
30:28 and the
30:29 vocational education
30:32 basically for the poorest.
30:34 That,
30:35 that was the,
30:36 the,
30:36 the starting.
30:38 Uh situation.
30:40 Then,
30:41 uh,
30:42 Many years
30:43 after that,
30:44 uh
30:45 DOC
30:46 and INACAP that are the largest uh institutions in Chile in
30:52 techno technical education and vocational education
30:56 were created in the late
30:58 60s
30:59 and uh
31:00 in a
31:02 Intermediate area uh
31:06 uh DO uh was uh focused on the illiterate
31:10 adults.
31:10 Uh it was uh
31:12 basically an initiative
31:14 of students,
31:16 uh Universia Cattolica students
31:19 that uh uh in this,
31:21 in this context of the,
31:23 the 60s,
31:25 Cuban revolution,
31:27 uh
31:27 uh
31:28 the Catholic Church,
31:30 uh
31:31 Uh,
31:32 more,
31:32 more pro
31:34 progress uh progressive and,
31:36 and that,
31:37 uh,
31:38 that was,
31:38 that was the context
31:40 and,
31:40 uh,
31:40 in AAP,
31:41 uh,
31:41 on the other hand,
31:42 it was uh initiative of the,
31:45 of the government to,
31:46 to,
31:47 to help the indus industrialization.
31:50 Basically that,
31:51 that was the,
31:53 the beginning.
31:55 Uh,
31:57 well,
31:57 uh,
31:58 as I said,
31:59 uh,
32:00 But,
32:01 but after that,
32:02 after that in,
32:03 in,
32:04 in,
32:04 since 1973 to,
32:07 to,
32:08 to 1980,
32:09 there was a,
32:11 a turmoil in,
32:12 in Chile and walk in
32:15 was in,
32:16 in some,
32:17 some way an oasis uh in the higher education,
32:21 not,
32:21 not,
32:21 it was not higher education in the educational system.
32:25 Again,
32:25 and then it started to
32:27 experiment in a small scale
32:30 with teaching methods,
32:32 OK.
32:33 Uh
32:35 In the,
32:36 in 1980,
32:37 there was a change,
32:38 uh,
32:39 a formal change,
32:40 a very important change in the,
32:42 in the,
32:43 in
32:43 Chile,
32:44 uh,
32:45 when,
32:45 uh,
32:46 because the,
32:47 the,
32:47 the schooling
32:49 uh
32:50 had increased a lot
32:52 uh and uh most people
32:55 knew how to write and were not illiterate anymore.
33:00 And uh there was a higher educational reform that,
33:04 that was very important.
33:07 At the very beginning,
33:08 very
33:09 mild with uh
33:11 small financing
33:13 for this,
33:13 this area.
33:15 Uh but uh it was very important and has a lot to do with,
33:19 with what uh Sebastian was mentioning before,
33:23 uh,
33:23 about the increasing,
33:25 in the,
33:25 in the enrollment of,
33:27 of higher education.
33:30 I mean.
33:32 OK.
33:33 Well,
33:33 let me talk,
33:34 basically,
33:35 my talk uh focuses uh in,
33:37 in a,
33:38 in a consolidated period.
33:40 That,
33:40 that's the idea I think it's,
33:42 it's very important to,
33:44 to look at the,
33:45 at the evolution of higher education in Chile
33:49 because it started
33:51 for one
33:53 in,
33:53 in one country where illiteracy was very high
33:58 and then it's moving.
34:01 To another country,
34:02 let's say another country where at least uh uh schooling was uh
34:08 much um almost
34:11 Complete.
34:12 So,
34:14 so in,
34:14 in 2010,
34:16 I,
34:17 I would say that,
34:18 that DOOC is a well-established institution in a relatively consolidated sector.
34:25 Uh
34:25 but
34:26 uh the diagnosis,
34:28 internal diagnosis
34:31 reflected in,
34:31 in,
34:32 in the stra strategic plan uh.
34:36 For the period
34:38 2016 to,
34:40 to 2021
34:43 reveals something that is,
34:45 is,
34:45 is worth uh
34:47 understanding and,
34:48 and it's a good lesson I think
34:51 for,
34:51 for other experiences.
34:53 Uh
34:54 uh it was
34:56 As I said,
34:57 uh,
34:57 uh,
34:58 relatively consolidated,
34:59 it was huge,
35:01 but,
35:02 but,
35:02 uh,
35:03 it was looking and changing
35:06 um
35:07 the,
35:07 the,
35:08 the administration methods
35:10 in,
35:10 in the following terms.
35:12 First,
35:13 it defined one.
35:15 Objective.
35:16 It,
35:16 it doesn't mean that it had only one objective,
35:19 but,
35:20 but it,
35:20 it focused in one objective that was
35:24 employment
35:25 of the enrolled peop uh of the enrolled students.
35:29 That means,
35:31 as,
35:31 as you will,
35:32 as you can see in the,
35:34 in the official data
35:35 that uh many times the,
35:37 the,
35:37 the employment uh of,
35:40 of
35:41 these institutions
35:43 are measured by um
35:46 uh those graduated.
35:49 But that,
35:49 that is tricky because when you,
35:52 you focus on
35:53 the enrollment,
35:54 I mean the employment rate
35:56 of those
35:57 enrolled,
35:59 you are,
35:59 uh you,
36:00 you are in charge of dropouts,
36:03 something that is,
36:04 is very important.
36:05 So,
36:06 so that's,
36:07 that's,
36:07 uh,
36:08 that,
36:08 that issue has not only implication for retention policies,
36:13 but also for defining careers
36:16 and vacancies.
36:18 Um
36:19 Something that,
36:20 that requires a close relationship with the private sector.
36:25 For,
36:25 for example,
36:26 uh,
36:26 let me give you a couple of examples,
36:29 uh,
36:30 vacancies
36:31 in the,
36:31 in tourism,
36:32 in tourism careers,
36:34 students like tourism.
36:36 Everybody
36:38 wants to be uh in that career,
36:41 but
36:42 the employment rate is low.
36:44 So,
36:45 Vacancies in that area were reduced while vacancies in logistics.
36:52 Very few students want logistics because it's more difficult,
36:56 it's more
36:57 um it's,
36:58 it's less attractive,
37:00 OK.
37:01 But,
37:01 but in terms of employment,
37:03 that's where,
37:04 where the,
37:05 the focus is.
37:06 Uh female students
37:08 love
37:09 health careers
37:10 that have,
37:11 have
37:12 a lot of,
37:13 uh,
37:13 have,
37:14 have a high employment rates
37:17 and low salaries,
37:18 OK.
37:19 So,
37:21 There was a,
37:22 an effort,
37:23 a direct effort to,
37:24 to move uh
37:25 uh female students from those careers to logistics,
37:30 to telecommunications to uh that kind of things.
37:35 Secondly,
37:36 uh,
37:37 it was
37:38 clearly
37:39 identified.
37:40 They,
37:41 they have,
37:41 uh,
37:42 we have identified for a long period.
37:46 A bias
37:47 in favor of universities compared with vocational technical education.
37:52 Think that we are talking now
37:55 about uh the work that is a post-secondary
38:00 education.
38:01 So it's,
38:01 it's not university,
38:03 but it's not
38:04 uh
38:06 Basic education
38:08 and,
38:08 and perception,
38:09 social perception and financing was biased.
38:12 Uh,
38:13 so there was a,
38:15 uh,
38:15 uh,
38:15 an effort and a consistent effort to,
38:18 to,
38:19 to influence
38:21 public policy because it's in public policy where
38:24 you put the money in that,
38:26 in that uh
38:27 terms.
38:29 In that effort,
38:31 uh,
38:32 uh,
38:32 there was uh something uh difficult to,
38:35 to,
38:35 to argue and,
38:37 and walk and,
38:38 and,
38:38 uh,
38:39 present that,
38:40 that was something that is
38:43 present in
38:46 most experiences that I know.
38:48 There are some good institutions in technical
38:51 education.
38:52 And a lot of very bad technical uh institutions.
38:57 And when
38:59 all,
39:00 all,
39:01 all institutions uh
39:02 are under the same umbrella,
39:05 so it's very difficult to promote
39:08 higher financing and,
39:09 and so on.
39:10 So,
39:11 that's,
39:11 that uh something uh.
39:13 Very important.
39:14 There was something also in that,
39:17 that uh
39:19 uh
39:19 idea of promoting
39:22 higher technical education,
39:24 something that,
39:24 that,
39:25 that was
39:26 in a,
39:26 in a
39:28 direction that was contrary to most uh
39:33 institutions in that time,
39:35 to say that
39:36 higher technical education is not university.
39:40 It's not university,
39:41 it's something graduates can complement,
39:45 but they are not substitutes uh because when you think they are substitutes and,
39:51 and,
39:51 and you can
39:52 see from the experience of Chile,
39:55 many technical institutions were trying to
39:59 look like universities and that's
40:02 the worst thing
40:04 you can do because you do something
40:07 you don't know.
40:08 OK.
40:09 Uh,
40:09 so,
40:10 That's uh,
40:12 and,
40:12 and a third,
40:13 a big issue,
40:16 we are talking now
40:17 an institution with nearly
40:20 100,000 students,
40:23 2500 staff,
40:25 and over 4000 teachers,
40:28 OK?
40:29 So
40:30 we needed,
40:31 if we,
40:31 we have to think
40:33 or if,
40:34 if you have to think in quality,
40:36 you have to standardize in some way,
40:39 OK.
40:40 You are teaching too many and
40:42 when,
40:42 when uh
40:44 a quality evaluation,
40:45 qua quality assessment,
40:47 uh
40:47 Uh,
40:48 when,
40:49 when,
40:49 uh,
40:50 the,
40:50 you evaluate quality,
40:53 you in general
40:54 consider the worst
40:56 campus,
40:57 the worst career,
40:57 so you need to standardize.
41:00 Um,
41:01 so in that,
41:02 in that,
41:02 uh,
41:04 uh,
41:04 in,
41:04 with that purpose,
41:06 uh,
41:07 had
41:08 a very in the,
41:10 in,
41:11 in the,
41:11 in the beginning of this,
41:12 this
41:13 period.
41:14 A,
41:15 a focus on evaluation,
41:18 project evaluation,
41:19 its own project evaluation,
41:21 created uh
41:22 uh uh uh analytical,
41:25 um,
41:27 uh,
41:27 analytical unit
41:29 to
41:30 evaluate projects
41:32 and to act as a counterpart of
41:35 external project evaluations.
41:37 Think in an institution.
41:40 With $300 million
41:44 budget.
41:46 You can do a lot of things and many things are bad ideas.
41:51 Uh,
41:51 so,
41:52 so you have to cut it,
41:53 you have to evaluate it and that,
41:54 that,
41:55 that thing was,
41:56 was very,
41:57 very critical.
41:59 Um.
42:01 Let me say,
42:02 uh,
42:04 Product of that,
42:05 uh,
42:06 uh,
42:06 and a long history,
42:08 uh,
42:09 Duo got the highest,
42:11 um,
42:13 uh.
42:13 Possible,
42:14 uh,
42:15 quality evaluation
42:17 in,
42:17 in,
42:18 in Chile.
42:19 OK.
42:20 Three institutions
42:21 had that,
42:22 that evaluation,
42:23 the highest,
42:24 University of Chile,
42:26 Universia Cattolica,
42:27 and DAC,
42:27 OK.
42:28 And that,
42:28 that was difficult.
42:29 It was,
42:30 it was the only non-university institution
42:34 that,
42:34 that uh had a,
42:36 a purpose and,
42:37 and that uh that um
42:40 uh focus.
42:41 I think that,
42:42 that,
42:42 that was very important.
42:44 Uh,
42:44 in,
42:44 in that line,
42:46 in,
42:46 in that line,
42:47 uh,
42:48 uh,
42:49 The focus on employment,
42:52 the role of,
42:53 of,
42:53 um,
42:55 of private sector entrepreneurs was key.
42:59 And uh
43:00 well,
43:01 Always you,
43:02 you,
43:03 you,
43:03 you have had something in,
43:06 in that,
43:06 that uh sector.
43:08 Uh every institution says
43:10 there are some
43:12 evidence of revealed preferences finally,
43:15 OK.
43:15 Uh uh
43:16 uh uh uh uh
43:19 to,
43:19 to the two of the largest uh
43:22 firms in Chile
43:24 donated over
43:26 $15,000 million.
43:29 Uh,
43:29 here we have something made for one of those institutions.
43:35 It created the Campus Arauco in the south of Chile,
43:38 uh,
43:39 but not only
43:41 there is uh another campus,
43:43 uh,
43:44 Uh,
43:45 not only they,
43:46 they gave,
43:47 uh,
43:48 uh,
43:49 money,
43:49 but they
43:50 participate.
43:51 Directly in the teaching
43:54 and
43:55 providing instructors
43:57 and,
43:57 uh,
43:58 and uh
43:59 a
44:00 part of the plan and that,
44:02 that's the most expensive and most significant
44:06 uh thing.
44:07 There is,
44:08 well,
44:08 I'm,
44:09 I'm there,
44:09 but it's,
44:10 it's not the idea that,
44:11 that,
44:12 uh,
44:13 I'm,
44:13 I'm going to talk about me,
44:15 but,
44:16 but that,
44:17 that photo.
44:18 is a price that uh got to be,
44:21 be
44:22 given by the main entrepreneurial uh association in Chi in Chile.
44:29 So reflecting the link between
44:32 the historical link
44:34 uh
44:35 between the institution and,
44:37 and the,
44:39 uh the,
44:39 the,
44:40 the private firms that,
44:41 that is
44:42 key.
44:45 So,
44:46 uh,
44:47 well,
44:48 uh,
44:48 new challenges.
44:50 I'm,
44:50 I'm,
44:50 I'm talking about,
44:52 uh,
44:53 pre-COVID,
44:55 OK.
44:55 So,
44:56 so,
44:57 uh,
44:58 uh,
44:58 well,
44:59 there were two
45:01 main,
45:01 uh,
45:03 Uh,
45:04 challenges,
45:05 uh,
45:05 updating laboratories,
45:07 that's always,
45:08 that always occur.
45:10 Everybody needs more,
45:12 uh,
45:13 laboratories,
45:14 uh,
45:15 uh,
45:15 mechanic areas,
45:17 etc.
45:18 And I,
45:19 I ironically say that's the easy part,
45:22 uh,
45:23 and the,
45:23 the difficult part is the curriculum,
45:26 the hard part.
45:27 The easy
45:28 Uh,
45:29 part,
45:29 I,
45:30 I,
45:30 uh,
45:31 I,
45:31 I said,
45:32 uh,
45:33 is,
45:33 is very expensive,
45:34 really,
45:35 but at least
45:38 Page 11.
45:41 At least,
45:42 uh,
45:44 Everybody
45:45 wants to
45:47 travel,
45:47 know new experiences,
45:49 uh,
45:50 know what kind of uh
45:53 things we need,
45:55 and you only need money.
45:58 Because it's very expensive,
45:59 OK?
46:00 If you,
46:00 if you,
46:01 if you want to have,
46:02 for instance,
46:04 a,
46:04 a mechanic uh uh uh mechanic uh tire,
46:08 I'm sorry,
46:09 I forgot.
46:11 Yeah,
46:11 uh,
46:12 you,
46:12 you need cars but you don't need
46:16 old cars dissembling uh old cars,
46:19 OK?
46:20 You must have
46:22 a new car
46:23 made to teach.
46:26 Which is more expensive,
46:28 OK,
46:28 and must be a very
46:30 uh
46:31 last model electric cars,
46:33 for instance,
46:34 and,
46:35 and it's,
46:36 it's not the price that you buy a,
46:39 uh,
46:40 an electric car.
46:41 These cars are made.
46:44 To teach.
46:45 So
46:46 they,
46:46 they are special.
46:48 I'm showing there
46:49 some,
46:51 some um
46:52 uh
46:53 those,
46:53 those uh things that you can practice,
46:57 uh
46:59 health things,
46:59 OK.
47:00 They,
47:01 they breathe,
47:02 they,
47:02 they,
47:03 they complain,
47:05 they,
47:05 and they are
47:07 dolls or something like that.
47:09 So,
47:09 so it's very expensive.
47:15 Well,
47:15 the difficult part is that of the curriculum.
47:18 Uh,
47:19 uh,
47:20 you,
47:20 you,
47:20 and,
47:20 and you're going to understand me,
47:22 I'm finishing almost,
47:24 uh,
47:25 because,
47:26 uh,
47:27 you need to change
47:29 things that
47:30 not only require money
47:32 but require
47:34 More thinking,
47:35 is,
47:35 is,
47:36 is more difficult,
47:37 require uh
47:38 more people,
47:40 uh
47:40 OK.
47:41 Uh,
47:42 and,
47:42 and let's think in,
47:44 in,
47:45 in,
47:46 this is,
47:47 this is the challenge.
47:49 We need to provide some
47:51 abilities and competences
47:54 uh that
47:55 don't become,
47:56 become obsolete.
47:58 Very quickly.
47:59 That's difficult.
48:00 If you,
48:01 if you teach,
48:02 uh,
48:02 if you teach uh
48:04 mechanics or,
48:05 or whatever,
48:06 uh,
48:07 that's going to be obsolete very quickly.
48:10 So,
48:11 so you,
48:12 you need to provide other competences uh that are
48:16 uh
48:17 that are
48:18 difficult.
48:19 And,
48:19 and we,
48:21 Duoc made a lot of service,
48:24 uh,
48:25 what kind of competences were needed.
48:29 Uh,
48:29 and,
48:30 and,
48:31 uh,
48:32 and we had to,
48:33 uh,
48:34 introduce.
48:36 Some,
48:37 some,
48:37 uh,
48:38 standard
48:39 er
48:40 to
48:41 put those competences
48:43 uh there.
48:45 There is a huge discussion,
48:47 a lot of literature
48:49 and uh
48:51 many guys or,
48:53 or there are different,
48:54 uh,
48:55 uh,
48:56 well,
48:56 a discussion
48:57 which,
48:58 which,
48:58 uh
48:59 Uh,
49:00 competence framework should we take?
49:03 That's,
49:04 that's,
49:04 uh,
49:05 uh,
49:06 you,
49:06 you don't finish that conversation,
49:09 OK.
49:09 So
49:10 we ascribe
49:11 to one competence framework,
49:14 uh.
49:15 To,
49:16 just to have some measure metrics to uh
49:21 to,
49:21 to,
49:22 to evaluate,
49:23 to assess
49:24 uh changes that,
49:26 that's
49:26 very important
49:28 to
49:29 asscribe to one.
49:30 We,
49:31 we didn't,
49:32 uh,
49:34 well,
49:35 a lot of guys uh of uh uh
49:37 uh
49:40 A lot of uh consultants
49:43 suggest us
49:44 to create our own
49:47 uh framework.
49:48 We are too big,
49:50 we don't need to follow,
49:52 but
49:52 that has a little problem that,
49:54 that when you
49:57 Do your own framework,
49:59 you cannot compare.
50:00 You,
50:01 you,
50:01 uh,
50:01 so it's more difficult to evaluate.
50:03 So,
50:04 so
50:05 we follow
50:06 uh uh uh.
50:08 Uh,
50:09 the training,
50:10 the training,
50:12 uh,
50:12 competence framework
50:13 and
50:14 we define those metrics and
50:17 we,
50:18 we create a baseline with
50:20 30,000 students,
50:22 OK.
50:23 We,
50:23 we assess them and,
50:25 and,
50:25 uh,
50:26 we start to,
50:27 to,
50:28 to
50:31 To,
50:32 to make a curriculum reform to introduce
50:36 those things we needed.
50:38 Uh,
50:39 8800 teachers were trained,
50:43 those numbers are,
50:44 are crazy,
50:45 but the,
50:45 the,
50:46 the institution is,
50:47 is,
50:47 is very,
50:49 uh,
50:49 there is the baseline.
50:52 And let me finish with as a very simple uh case,
50:57 something that,
50:58 that is very
51:00 nice,
51:01 uh,
51:01 but is,
51:02 is something,
51:03 it reflects
51:04 the difficulties
51:06 uh you have when you want to introduce one of those abilities.
51:11 Uho didn't introduce all the framework.
51:14 It started with
51:16 one.
51:18 One,
51:19 ability,
51:20 then another,
51:21 because
51:22 to change everything,
51:24 uh,
51:24 is makes much more difficult to evaluate
51:27 and to,
51:28 to retract if,
51:30 if the,
51:30 if the,
51:31 if the idea is bad.
51:33 So,
51:33 uh,
51:34 critical thinking in,
51:35 in the classroom.
51:38 So there,
51:39 um,
51:41 uh,
51:41 critical thinking defined as the capacity to
51:44 derive logical conclusions to solve problems that,
51:47 that's a standard.
51:49 It presented
51:50 basically
51:51 two problems.
51:53 One,
51:54 they need
51:55 to develop.
51:58 Uh,
51:59 uh,
52:01 develop it in,
52:02 in the language courses
52:05 because
52:05 this is not mathematical capacity.
52:08 It has to do much more with,
52:10 with communications.
52:12 With communication,
52:14 not with mathematics.
52:15 So
52:16 uh in language,
52:18 we have to do it that,
52:20 but,
52:21 but,
52:21 uh,
52:22 this,
52:22 that,
52:23 that's uh is much more difficult to improve it in short periods,
52:27 and more difficult to evaluate
52:29 and,
52:30 and,
52:30 um,
52:31 uh,
52:32 another problem that has,
52:33 uh,
52:34 that,
52:34 that,
52:35 uh
52:36 That,
52:37 the thing is that
52:39 Evaluating critical thinking.
52:42 Uh,
52:43 it's very difficult because
52:45 critical thinking,
52:47 uh,
52:47 has to do with the context.
52:49 Let me show you a couple of,
52:51 of,
52:51 uh,
52:53 slides
52:54 that
52:55 reflect that.
52:56 This is uh,
52:57 uh,
52:58 another,
52:58 uh,
52:58 is uh,
52:59 the,
53:00 the person or the team we hired to,
53:03 to do this thing
53:05 had worked in,
53:06 in,
53:07 in,
53:07 in China,
53:08 in Asia,
53:09 and in other countries,
53:10 in Spain.
53:12 So,
53:13 uh,
53:14 they,
53:15 they,
53:15 this is uh from,
53:16 from them,
53:17 uh,
53:18 they,
53:18 they evaluate,
53:19 uh,
53:20 critical thinking,
53:21 asking,
53:22 uh,
53:23 Students,
53:25 uh,
53:26 the,
53:26 the
53:28 I don't know,
53:28 so the,
53:29 the world,
53:30 uh,
53:30 go around the world in 88 days.
53:33 It's a
53:35 Julius Verne's,
53:36 uh,
53:37 uh,
53:38 classical book,
53:39 you know,
53:39 all,
53:40 uh,
53:41 so after reading that,
53:43 that short story,
53:45 uh,
53:46 they,
53:46 the students were asked,
53:48 uh,
53:48 do you think it's possible to go around the world in 8,
53:52 80 days?
53:53 And uh well,
53:55 uh,
53:56 it was a systematic
53:59 difference in two groups
54:01 of students,
54:03 those that,
54:03 that uh were,
54:05 let's say richer,
54:07 they answer perfectly
54:09 and the poorest,
54:11 not
54:12 very bad,
54:13 both read the same thing.
54:15 And,
54:15 and when,
54:16 when
54:18 the students were asked,
54:19 uh,
54:19 why,
54:21 how do you
54:22 Reason to conclude that uh it is possible.
54:26 Well,
54:27 last week we went to New York,
54:29 uh,
54:30 that,
54:30 that was the kind of answers.
54:32 So
54:33 there is a contextual
54:34 uh
54:35 uh thing that has
54:37 little to do with uh,
54:38 with uh
54:40 with uh the critical thinking,
54:42 but only with its context.
54:45 Same thing in China.
54:48 There were,
54:48 were some,
54:49 some questions about this story and uh the,
54:52 the question was the,
54:54 what about the,
54:55 the
54:56 Martin de Bland and Orlando,
54:59 the,
55:00 the,
55:01 and,
55:02 and uh those,
55:03 those kids
55:04 didn't
55:06 get what,
55:06 what,
55:07 what was a bla a blonde guy,
55:10 they,
55:11 they didn't know.
55:12 So the answers were but.
55:14 What I,
55:15 what I want to say with that
55:17 is that we,
55:19 we had to create our own
55:22 uh metric and,
55:23 and there we couldn't go to the literature
55:27 or the,
55:28 or because
55:29 there is
55:31 little investigation,
55:31 little research on that
55:33 and
55:34 uh the,
55:34 the test.
55:35 are contextual.
55:36 So
55:37 in that,
55:38 that group created valid test
55:41 uh uh had a huge uh effort to,
55:47 to evaluate
55:49 results
55:50 and they're working on that,
55:52 in that,
55:53 in,
55:53 in this moment.
55:55 Let me
55:58 Let me conclude saying a couple of things,
55:59 perhaps,
56:00 uh,
56:01 um.
56:02 Uh,
56:02 a main conclusion,
56:04 general conclusion is that,
56:05 uh,
56:06 higher vocational education is key.
56:08 We,
56:09 we know that,
56:10 but
56:10 basically,
56:11 uh,
56:13 not all institutions
56:15 are
56:16 equally good
56:17 and,
56:18 uh,
56:18 and if,
56:19 if you don't,
56:21 uh,
56:22 uh,
56:24 split
56:25 those goods
56:26 from
56:27 the good from the bad,
56:28 you are going to
56:30 do bad public policy.
56:32 The lower tail in quality is
56:34 too long,
56:35 OK.
56:36 Uh,
56:37 perhaps,
56:37 uh,
56:38 I would remark that the way technical,
56:42 um,
56:43 Uh,
56:45 institutions,
56:45 uh,
56:47 Uh,
56:48 uh,
56:49 there is some lesson,
56:50 uh,
56:51 that is very valid and,
56:52 uh,
56:53 it's a more a question or,
56:55 or some thoughts that,
56:57 that,
56:57 that I have.
56:58 They teach
57:00 in a different way than universities,
57:03 uh,
57:03 or in,
57:04 in,
57:04 in,
57:04 in
57:06 schools.
57:07 This is valid also for
57:09 vocational education or technical education at scholar level.
57:14 They teach,
57:15 they can teach the,
57:17 the heat transfer equation.
57:21 With a,
57:22 with a,
57:24 with a
57:26 ther
57:26 thermometer,
57:27 a,
57:28 a blowtorch,
57:29 and uh,
57:30 and a brick,
57:31 a brick
57:33 is,
57:34 or you can learn the same equation with a book.
57:38 Students,
57:39 most students
57:41 like more the first way,
57:43 the practical thing.
57:44 So
57:45 perhaps
57:46 we have to,
57:47 to think what are uh going to be the,
57:50 the right way to teach
57:54 those students that,
57:55 that
57:56 have a lot of stimulation,
57:58 uh,
57:59 they,
57:59 they have a
58:01 short uh
58:02 period uh of concentration.
58:05 And,
58:05 and that's uh uh a
58:08 main thing we,
58:09 we,
58:10 perhaps
58:11 we could
58:12 learn from this kind of education to other
58:16 uh more general education.
58:18 Thank you very much.
58:22 Muta gracia Ricardo,
58:24 before handing to,
58:25 to Joyce,
58:25 let me just say that
58:27 I think there are 22 elements,
58:29 uh,
58:31 that,
58:31 that I see as relevant.
58:32 The first one,
58:33 of course,
58:34 it's that there's a lot of very idiosyncratic elements in each educational system.
58:40 Um,
58:41 you know,
58:42 in,
58:42 in Chile,
58:42 and other countries,
58:44 so,
58:44 uh,
58:45 we need to always have this in mind,
58:46 you know,
58:47 there are lessons that we can extract.
58:48 There's also aspects that are very local,
58:50 very specific to each country.
58:52 So I think the big challenge is,
58:54 uh,
58:54 which is my number 2 point to,
58:56 to how to,
58:57 uh,
58:57 in our view,
58:59 uh,
58:59 walking the talk and really investing strongly in education.
59:03 In public education,
59:04 in particular in Argentina we have decided to allocate 6% of the public
59:10 national GDP
59:12 to education which is very important so.
59:15 Investing in education a lot as you make the case,
59:18 uh,
59:18 learning from the different systems and from the different countries
59:22 and trying then to,
59:24 to consider how to
59:26 implement this to the different uh realities,
59:28 uh,
59:29 trying to really push for development which is I think,
59:32 uh,
59:32 the goal of this uh very important
59:34 WUDR that is coming.
59:36 But anyway,
59:37 thank you very much,
59:37 uh,
59:38 Ricardo,
59:38 I will hand over to,
59:39 to Joyce for the last minute.
59:43 Thanks so much,
59:44 Cecilia,
59:45 for,
59:45 for sharing.
59:45 I really appreciate it and thanks,
59:46 Sebastian Ricardo for the great,
59:48 great presentations.
59:49 Um,
59:50 we're hoping to have some time for questions.
59:52 I see we've run out of time.
59:53 Um,
59:54 so I,
59:54 I think maybe for those that need to log off,
59:57 uh,
59:57 please,
59:57 by all means,
59:58 um,
1:00:00 But Ricardo and Sebastian,
1:00:01 with your permission,
1:00:02 if you do want to stay a few minutes for those that would like to ask questions,
1:00:05 maybe we can give them a chance,
1:00:06 but,
1:00:07 uh,
1:00:07 just quickly before,
1:00:08 um,
1:00:09 so for those that do need to log off,
1:00:10 just a couple of announcements on our upcoming seminars.
1:00:14 Um,
1:00:14 we have one next week on November 1st.
1:00:16 It's uh Yang Hongxin from the IMF and,
1:00:19 and Sina Atta from the Federal Reserve.
1:00:20 That are presenting on trade firms and economic development.
1:00:24 And the following week on November 8th,
1:00:26 we have Moon Xia Lee on,
1:00:27 on Korea's growth miracle and,
1:00:29 and slowdown.
1:00:30 So please,
1:00:30 uh,
1:00:31 feel free to join us for those and the,
1:00:33 um,
1:00:34 the announcements on,
1:00:35 and the details are always on our website,
1:00:37 as will the recording and the presentations from,
1:00:40 from today's seminar.
1:00:41 Um,
1:00:42 so,
1:00:42 so thank you again and then again,
1:00:44 for those that need to log off,
1:00:45 please,
1:00:45 uh,
1:00:45 please do so.
1:00:46 For those that have,
1:00:47 uh,
1:00:47 would like to stay on and,
1:00:48 and just ask a few questions,
1:00:50 please feel free to raise your hand.
1:00:52 Um,
1:00:52 and while you do so,
1:00:54 Uh,
1:00:55 Sebastian,
1:00:55 I think you had already a couple of questions in the chat.
1:00:59 Um,
1:00:59 Lucia asked,
1:01:00 what are the mechanisms that allow the progress
1:01:03 on social mobility,
1:01:04 and Stefan,
1:01:05 uh,
1:01:05 which other universities in Chile
1:01:07 assure this important social mobility.
1:01:09 So maybe if you wanna
1:01:10 address those while,
1:01:11 um,
1:01:12 others come in if they have questions.
1:01:17 Sure,
1:01:17 sure.
1:01:18 We can,
1:01:18 I can talk hours about this topic.
1:01:20 So no,
1:01:21 but uh,
1:01:21 but I,
1:01:22 I like that both,
1:01:22 both questions are um related to social mobility.
1:01:27 Uh,
1:01:27 we,
1:01:28 we are not doing,
1:01:29 I mean,
1:01:30 I didn't show you anything related to social mobility in my presentation or is in,
1:01:34 in the paper,
1:01:35 but I happen to have another one
1:01:37 which is a side paper that I shared,
1:01:40 in the,
1:01:40 in the chat which is
1:01:42 educational mobility across 3 generations in Latin American countries.
1:01:46 So,
1:01:47 but let,
1:01:48 let,
1:01:48 let me go back to the,
1:01:49 to the questions themselves.
1:01:50 So one is,
1:01:52 what are the mechanisms that allow the progress of social mobility
1:01:56 and um,
1:01:58 well,
1:01:58 one is super important and it's well documented is access to
1:02:03 uh uh higher education.
1:02:05 Right?
1:02:06 So it's true that I didn't talk about uh social mobility in my presentation,
1:02:11 but I can understand where you're heading with this.
1:02:14 And
1:02:15 basically,
1:02:16 I,
1:02:16 I think it's well documented at least in Chile,
1:02:19 but I think that this applies to our
1:02:22 uh Latin American countries
1:02:24 in particular and in general to developing countries.
1:02:28 If you
1:02:29 are able to attend
1:02:31 one of the most prestigious,
1:02:34 um,
1:02:35 colleges slash degrees in your country,
1:02:37 I think that's basically it.
1:02:39 You're probably not gonna be
1:02:41 part of the top 1% because like,
1:02:44 uh,
1:02:44 that's,
1:02:45 uh,
1:02:45 there is this,
1:02:47 uh,
1:02:47 glass ceiling above,
1:02:49 uh.
1:02:50 Um,
1:02:51 but that,
1:02:51 that is still gonna produce a lot of social
1:02:54 mobility and I think that that's one of the main
1:02:57 mechanisms that we
1:02:58 have today that is
1:03:00 observable,
1:03:01 and so I think that what,
1:03:03 what has happened in Chile is that we have improved on that,
1:03:06 on that metric.
1:03:08 And then there is something uh like the second derivative which is I would,
1:03:13 I would call it an intensive margin.
1:03:17 Uh,
1:03:18 way of looking at this,
1:03:20 one of the,
1:03:21 is the extensive margin.
1:03:22 The extensive margin is like,
1:03:24 do you enroll.
1:03:27 At higher education institutions,
1:03:29 yes or no,
1:03:30 and 50 years ago that was super,
1:03:32 super low fraction of the population
1:03:34 had the opportunity.
1:03:36 Today that's
1:03:37 pretty high,
1:03:38 even for low socioeconomic status.
1:03:40 But now,
1:03:40 the next derivative,
1:03:41 the intensive margin derivative is like where
1:03:44 are you gonna enroll
1:03:45 and I think we,
1:03:46 and that,
1:03:47 and,
1:03:47 and that is what is gonna
1:03:48 be the
1:03:49 main mechanism behind social mobility and we
1:03:52 need to do
1:03:53 much more in that regard.
1:03:55 So yeah.
1:03:56 Uh,
1:03:56 I can talk for hours,
1:03:57 so I'm gonna stop there.
1:04:03 Great.
1:04:03 Thank you,
1:04:03 Sebastian.
1:04:04 Um,
1:04:05 any,
1:04:06 any other questions?
1:04:08 Either Sebastian or Ricardo.
1:04:13 OK,
1:04:13 great.
1:04:14 All right.
1:04:14 Well,
1:04:14 thank you once again and um
1:04:17 you know,
1:04:17 and feel free to,
1:04:18 to reach out to them after if you have questions as well.
1:04:20 And again,
1:04:20 the presentation recording will be on our website.
1:04:23 So thank you everyone and,
1:04:24 and have a nice day.
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