- Teks
- Sejarah
Propositions of Requisite Knowledge
Propositions of Requisite Knowledge
The first author answered/responded to the chemistry content of each of the 41 items that were obtained from the interviews. This was done to gain an understanding of what was required for a student to (a) understand, and/or (b) solve the item. In many cases, these two sets of requirements were different. As a result, two lists of propositions (statements) were generated for each of the 41 items: One set of propositions described what is required to simply solve the item correctly (“propositions for solving”) and one set described what is required to understand the concepts behind the item (“propositions for understanding”). See Figure 1 for examples of the two types of propositions that were generated for each item.
The propositions for understanding described the chemical theories and principles required to gain a full understanding of the phenomenon, while the propositions for solving did not involve any more detail than what was absolutely necessary to respond to the item correctly.
These propositions and equations were compiled and sent to the second and third authors for content validation. Propositions were negotiated until all authors agreed that the propositions listed represented the appropriate knowledge requirements for each teacher-generated assessment item. The first author (who was not previously familiar with the interviews) was responsible for the original development of the propositions so that the other authors would not skew the propositions of the items by knowing what the teachers’ goals were, as they were familiar with the previous interviews conducted. Propositions for all items can be found in the Supporting Information.
Comparisons
Using the propositions and summaries, we were able to determine the alignment of teachers’ goals and conclusions (data in the summaries) with what was assessed by the items (propositions). For each of the 41 items, we compared the summaries (capturing teachers’ descriptions viewed through a DDI lens) to the propositions with the aim of generating descriptors that effectively characterized the features of the data corpus. These descriptors were revised and tested as we applied them to more and more items. Through multiple iterations and discussion among the research team, categories became a list of codes that we systematically applied to each item. Originally, the authors set out to determine if the propositions that the first author created aligned or did not align with the teachers’ideas. However, reducing this to a dichotomy severely limited our understanding of data and the conclusions we could make.
Alternatively, we present the features that we examined in Table 1, which represent our coding scheme. Some codes originated as themes from the interviews collected, others arose out of the propositions that were created, and some were generated to apply to all items with the aim of capturing broader themes that could emerge. Each item was coded according to the binary outcome in Table 1. An example of this process is given in Figure 2, which shows the outcome based on the summary displayed in Figure 1.
The first author answered/responded to the chemistry content of each of the 41 items that were obtained from the interviews. This was done to gain an understanding of what was required for a student to (a) understand, and/or (b) solve the item. In many cases, these two sets of requirements were different. As a result, two lists of propositions (statements) were generated for each of the 41 items: One set of propositions described what is required to simply solve the item correctly (“propositions for solving”) and one set described what is required to understand the concepts behind the item (“propositions for understanding”). See Figure 1 for examples of the two types of propositions that were generated for each item.
The propositions for understanding described the chemical theories and principles required to gain a full understanding of the phenomenon, while the propositions for solving did not involve any more detail than what was absolutely necessary to respond to the item correctly.
These propositions and equations were compiled and sent to the second and third authors for content validation. Propositions were negotiated until all authors agreed that the propositions listed represented the appropriate knowledge requirements for each teacher-generated assessment item. The first author (who was not previously familiar with the interviews) was responsible for the original development of the propositions so that the other authors would not skew the propositions of the items by knowing what the teachers’ goals were, as they were familiar with the previous interviews conducted. Propositions for all items can be found in the Supporting Information.
Comparisons
Using the propositions and summaries, we were able to determine the alignment of teachers’ goals and conclusions (data in the summaries) with what was assessed by the items (propositions). For each of the 41 items, we compared the summaries (capturing teachers’ descriptions viewed through a DDI lens) to the propositions with the aim of generating descriptors that effectively characterized the features of the data corpus. These descriptors were revised and tested as we applied them to more and more items. Through multiple iterations and discussion among the research team, categories became a list of codes that we systematically applied to each item. Originally, the authors set out to determine if the propositions that the first author created aligned or did not align with the teachers’ideas. However, reducing this to a dichotomy severely limited our understanding of data and the conclusions we could make.
Alternatively, we present the features that we examined in Table 1, which represent our coding scheme. Some codes originated as themes from the interviews collected, others arose out of the propositions that were created, and some were generated to apply to all items with the aim of capturing broader themes that could emerge. Each item was coded according to the binary outcome in Table 1. An example of this process is given in Figure 2, which shows the outcome based on the summary displayed in Figure 1.
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Propositions of Requisite KnowledgeThe first author answered/responded to the chemistry content of each of the 41 items that were obtained from the interviews. This was done to gain an understanding of what was required for a student to (a) understand, and/or (b) solve the item. In many cases, these two sets of requirements were different. As a result, two lists of propositions (statements) were generated for each of the 41 items: One set of propositions described what is required to simply solve the item correctly (“propositions for solving”) and one set described what is required to understand the concepts behind the item (“propositions for understanding”). See Figure 1 for examples of the two types of propositions that were generated for each item.The propositions for understanding described the chemical theories and principles required to gain a full understanding of the phenomenon, while the propositions for solving did not involve any more detail than what was absolutely necessary to respond to the item correctly.These propositions and equations were compiled and sent to the second and third authors for content validation. Propositions were negotiated until all authors agreed that the propositions listed represented the appropriate knowledge requirements for each teacher-generated assessment item. The first author (who was not previously familiar with the interviews) was responsible for the original development of the propositions so that the other authors would not skew the propositions of the items by knowing what the teachers’ goals were, as they were familiar with the previous interviews conducted. Propositions for all items can be found in the Supporting Information.ComparisonsUsing the propositions and summaries, we were able to determine the alignment of teachers’ goals and conclusions (data in the summaries) with what was assessed by the items (propositions). For each of the 41 items, we compared the summaries (capturing teachers’ descriptions viewed through a DDI lens) to the propositions with the aim of generating descriptors that effectively characterized the features of the data corpus. These descriptors were revised and tested as we applied them to more and more items. Through multiple iterations and discussion among the research team, categories became a list of codes that we systematically applied to each item. Originally, the authors set out to determine if the propositions that the first author created aligned or did not align with the teachers’ideas. However, reducing this to a dichotomy severely limited our understanding of data and the conclusions we could make.Alternatively, we present the features that we examined in Table 1, which represent our coding scheme. Some codes originated as themes from the interviews collected, others arose out of the propositions that were created, and some were generated to apply to all items with the aim of capturing broader themes that could emerge. Each item was coded according to the binary outcome in Table 1. An example of this process is given in Figure 2, which shows the outcome based on the summary displayed in Figure 1.
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Proposisi dari Requisite Pengetahuan
Penulis pertama menjawab / menanggapi isi kimia dari masing-masing 41 item yang diperoleh dari wawancara. Hal ini dilakukan untuk memperoleh pemahaman tentang apa yang diperlukan bagi siswa untuk (a) memahami, dan / atau (b) memecahkan item. Dalam banyak kasus, ini dua set persyaratan yang berbeda. Akibatnya, dua daftar proposisi (pernyataan) yang dihasilkan untuk masing-masing 41 item: Satu set proposisi dijelaskan apa yang diperlukan untuk hanya memecahkan item dengan benar ("proposisi untuk memecahkan") dan satu set dijelaskan apa yang diperlukan untuk memahami konsep di balik item ("proposisi untuk memahami"). Lihat Gambar 1 untuk contoh dari dua jenis proposisi yang dihasilkan untuk setiap item.
Proposisi untuk memahami menggambarkan teori kimia dan prinsip-prinsip yang diperlukan untuk mendapatkan pemahaman penuh dari fenomena tersebut, sedangkan proposisi untuk pemecahan tidak melibatkan detail lebih dari apa yang benar-benar diperlukan untuk menanggapi item dengan benar.
Ini proposisi dan persamaan dikumpulkan dan dikirim ke penulis kedua dan ketiga untuk validasi konten. Proposisi yang dinegosiasikan sampai semua penulis setuju bahwa proposisi terdaftar diwakili persyaratan pengetahuan yang sesuai untuk setiap item penilaian guru yang dihasilkan. Penulis pertama (yang sebelumnya tidak akrab dengan wawancara) bertanggung jawab untuk pengembangan asli dari proposisi sehingga penulis lain tidak akan condong proposisi item dengan mengetahui apa tujuan guru adalah, karena mereka akrab dengan wawancara sebelumnya yang dilakukan. Proposisi untuk semua item dapat ditemukan di Informasi Pendukung.
Perbandingan
Menggunakan proposisi dan ringkasan, kami mampu menentukan keselarasan tujuan guru dan kesimpulan (data dalam ringkasan) dengan apa yang dinilai oleh semuanya (proposisi). Untuk masing-masing 41 item, kami membandingkan ringkasan (menangkap deskripsi guru dilihat melalui lensa DDI) ke proposisi dengan tujuan menghasilkan deskriptor yang efektif ditandai fitur dari corpus data. Deskriptor tersebut direvisi dan diuji seperti yang kita diterapkan mereka untuk semakin banyak item. Melalui beberapa iterasi dan diskusi antara tim peneliti, kategori menjadi daftar kode yang kami sistematis diterapkan untuk setiap item. Awalnya, penulis berangkat untuk menentukan apakah proposisi bahwa penulis pertama dibuat selaras atau tidak sejajar dengan teachers'ideas. Namun, mengurangi ini untuk dikotomi sangat terbatas pemahaman kita tentang data dan kesimpulan kita bisa membuat.
Atau, kami menyajikan fitur yang kami diperiksa pada Tabel 1, yang merupakan skema pengkodean kami. Beberapa kode berasal sebagai tema dari wawancara yang dikumpulkan, yang lain muncul dari proposisi yang diciptakan, dan beberapa yang dihasilkan berlaku untuk semua item dengan tujuan menangkap tema yang lebih luas yang bisa muncul. Setiap item diberi kode sesuai dengan hasil biner dalam Tabel 1. Contoh dari proses ini diberikan dalam Gambar 2, yang menunjukkan hasil berdasarkan ringkasan ditampilkan pada Gambar 1.
Penulis pertama menjawab / menanggapi isi kimia dari masing-masing 41 item yang diperoleh dari wawancara. Hal ini dilakukan untuk memperoleh pemahaman tentang apa yang diperlukan bagi siswa untuk (a) memahami, dan / atau (b) memecahkan item. Dalam banyak kasus, ini dua set persyaratan yang berbeda. Akibatnya, dua daftar proposisi (pernyataan) yang dihasilkan untuk masing-masing 41 item: Satu set proposisi dijelaskan apa yang diperlukan untuk hanya memecahkan item dengan benar ("proposisi untuk memecahkan") dan satu set dijelaskan apa yang diperlukan untuk memahami konsep di balik item ("proposisi untuk memahami"). Lihat Gambar 1 untuk contoh dari dua jenis proposisi yang dihasilkan untuk setiap item.
Proposisi untuk memahami menggambarkan teori kimia dan prinsip-prinsip yang diperlukan untuk mendapatkan pemahaman penuh dari fenomena tersebut, sedangkan proposisi untuk pemecahan tidak melibatkan detail lebih dari apa yang benar-benar diperlukan untuk menanggapi item dengan benar.
Ini proposisi dan persamaan dikumpulkan dan dikirim ke penulis kedua dan ketiga untuk validasi konten. Proposisi yang dinegosiasikan sampai semua penulis setuju bahwa proposisi terdaftar diwakili persyaratan pengetahuan yang sesuai untuk setiap item penilaian guru yang dihasilkan. Penulis pertama (yang sebelumnya tidak akrab dengan wawancara) bertanggung jawab untuk pengembangan asli dari proposisi sehingga penulis lain tidak akan condong proposisi item dengan mengetahui apa tujuan guru adalah, karena mereka akrab dengan wawancara sebelumnya yang dilakukan. Proposisi untuk semua item dapat ditemukan di Informasi Pendukung.
Perbandingan
Menggunakan proposisi dan ringkasan, kami mampu menentukan keselarasan tujuan guru dan kesimpulan (data dalam ringkasan) dengan apa yang dinilai oleh semuanya (proposisi). Untuk masing-masing 41 item, kami membandingkan ringkasan (menangkap deskripsi guru dilihat melalui lensa DDI) ke proposisi dengan tujuan menghasilkan deskriptor yang efektif ditandai fitur dari corpus data. Deskriptor tersebut direvisi dan diuji seperti yang kita diterapkan mereka untuk semakin banyak item. Melalui beberapa iterasi dan diskusi antara tim peneliti, kategori menjadi daftar kode yang kami sistematis diterapkan untuk setiap item. Awalnya, penulis berangkat untuk menentukan apakah proposisi bahwa penulis pertama dibuat selaras atau tidak sejajar dengan teachers'ideas. Namun, mengurangi ini untuk dikotomi sangat terbatas pemahaman kita tentang data dan kesimpulan kita bisa membuat.
Atau, kami menyajikan fitur yang kami diperiksa pada Tabel 1, yang merupakan skema pengkodean kami. Beberapa kode berasal sebagai tema dari wawancara yang dikumpulkan, yang lain muncul dari proposisi yang diciptakan, dan beberapa yang dihasilkan berlaku untuk semua item dengan tujuan menangkap tema yang lebih luas yang bisa muncul. Setiap item diberi kode sesuai dengan hasil biner dalam Tabel 1. Contoh dari proses ini diberikan dalam Gambar 2, yang menunjukkan hasil berdasarkan ringkasan ditampilkan pada Gambar 1.
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- 1. Defining Criteria : on what bases wil
- pemberian rapot
- Good luck for my husband
- semoga allah selalu menjagamu wahai calo
- Good luck for my husband
- semoga allah selalu menjagamu wahai calo
- All right
- 1. Defining Criteria : on what bases wil
- apa kabar semua.
- Pusing tujuh keliling
- Dasar!! manusia PENCUNDANG.......
- Semoga cepat sembuh istriku sayang
- Yes,of course
- semoga makin sayang, makin cinta, terbai
- Yes,please
- mapenzi hopefully zaidi, upendo zaidi, b
- contoh inquiry and reply letter INQUIRY
- No,i'm afraid not
- All praises to allah
- contoh inquiry and reply letter INQUIRY
- Formative assessments are of paramount i
- tetapi saya menikmatinya
- Fake smile
- Can i
