Kua huri tēnei ao e noho nei tātou hei ao matihiko, kua kī i te hangarau, kua whakakahangia e te pūtaiao rorohiko. Kua whakahuria ngā marau katoa, me ngā momo tūmahi katoa e te hangarau me ngā pūmanawa rorohiko, mai i te pūtaiao me te rongoā ki te mātai hinengaro me te rangahau toi ataata. He hangarau matihiko ka kitea, puta noa i te ao. Kia whakamanatia, kia whai mōhio hoki ngā kirirarau, me mōhio rawa te whakatipuranga hou o ngā ākonga ki tēnei ao hangarau matihiko e noho nei rātou.
This is why Computational Thinking has been called the '21st Century Skill Set', and is important for everyone to learn. It is critical to understanding how the digital world works, for harnessing the power of computers to solve tough problems, and making great things happen! It also enables us to think critically about not just the benefits of certain technologies, but also the potential harm, ethical implications, or unintended consequences of these.
But what exactly is Computational Thinking? Let's have a look at a technical definition...
"Ko te "Whakaaro Rorohiko" tētahi momo tukanga whakaaro e whakamahia ki te wetewete i ngā āhuatanga o tētahi rapanga, me ngā otinga, kia whakatakotoria hei tauira e tika ana kia whakahaerengia e te rorohiko, i tētahi atu pūnaha whakahaere i te mōhiohio rānei."
Phew, it's quite a mouthful isn't it? But, as we like to say at CS Unplugged, it's just big words for simple ideas! 'Information-processing agent' means anything that follows a set of instructions to complete a task (we call this 'computing'). Most of the time this 'agent' means a computer or other type of digital device - but it could also be a human! We'll refer to it as a computer to make things a bit simpler. To represent solutions in a way that a computer can carry them out, we have to represent them as a step by step process - an algorithm. To create these algorithmic solutions we apply some special problem solving skills to. These skill are what make up Computational Thinking! And they are skills that are transferrable to any field.
Computational Thinking could be described as 'thinking like a Computer Scientist', but it is now an important skill for everyone to learn, whether they want to be a Computer Scientist or not! It's interesting, and important, to note that Computational Thinking, and Computer Science, aren't entirely about computers, they are more about people. You might think that we write programs for computers, but really we write programs for people - to help them communicate, find information, and solve problems.
Hei tauira, ka whakamahi pea koe i te taupānga o tō waea pūkoro ki te rapu i te ara ki te whare o tō hoa; he tauira papatono rorohiko te taupānga, ā, ko te waea pūkoro te "kaikawe tukatuka mōhiohio" e whakahaere ana i te papatono mā tātou. Ahakoa ko wai te tangata nāna nei te hātepe i hoahoa hei kimi i te ara pai rawa atu, me ngā āhuatanga katoa pērā i te atanga, ka pēhea hoki te whakaputu i te mahere, nāna i whakamahi i te whakaaro rorohiko hei hoahoa i te pūnaha. Heoi anō, kāore i hoahoatia e rātou mā te waea pūkoro noa iho; i hoahoatia e rātou hei āwhina i te tangata e whakamahi ana i te waea pūkoro.
Te Whakaaro Rorohiko kei roto i te CS Unplugged
Kei roto i ngā akomanga, me ngā wāhanga o CS Unplugged, he maha ngā hononga ki te Whakaaro Rorohiko. Mā te whakaako i te Whakaaro Rorohiko mā ngā mahinga o CS Unplugged e ako ai ngā ākonga ki te:
whakaahua i tētahi rapanga,
tautuhi i ngā meka nui hei whakaoti i tēnei rapanga,
whakawāhi i te rapanga ki ngā wāhanga mahi iti, arorau hoki,
whakamahia ngā wāwāhinga ki te waihanga i tētahi tukanga (hātepe) e whakaoti ai te rapanga,
kātahi ka aromātai i tēnei tukanga.
He pūkenga ēnei ka taea te whakawhiti atu ki marautanga kē, heoi anō, he tino hāngai ki te waihanga i ngā pūnaha hangarau matihiko me te whakaoti rapanga mā ngā āheitanga o te rorohiko.
Ka honohono, ka tautoko hoki katoa ēnei ariā Whakaaro Rorohiko, engari ko te mea nui kia mōhio kāore e kitea ngā āhuatanga katoa o te Whakaaro Rorohiko i roto i ia wāhanga ako, i ia akoranga rānei. Kua tīpako mātou i ngā hononga whakahirahira i roto i ia wāhanga ako, i ia akoranga hoki kia mātakitaki ai koe i ō ākonga e mahi ana.
He maha ngā tautuhinga mō te Whakaaro Rorohiko, heoi anō, mō te nuinga, ka kitea te huinga pūkenga e 5, e 6 rānei o ngā pūkenga whakaoti rapanga. Mō te hinonga Unplugged, kua whakatau mātou i ngā pūkenga Whakaaro Rorohiko e ono kei raro nei. Ka kitea whānuitia ēnei pūkenga i roto i ngā tuhinga rangahau; ka whakamāramatia ēnei kei raro, kei te mutunga hoki o ia akomanga Unplugged, me te whakamārama hoki i pēhea i tipu ai aua pūkenga i roto i ngā mahi kia kite ai koe i ngā hononga ki te Whakaaro Rorohiko.
Ngā Pūkenga Whakaaro Rorohiko
Te Whakaaro Hātepe
Algorithms are at the heart of Computational Thinking and Computer Science, because in Computer Science the solutions to problems are not simply an answer (e.g. '42', or a fact), they are algorithms. An algorithm is a step-by-step process that solves a problem or completes a task. If you follow the algorithm's steps correctly, you will arrive at a correct solution, even for different inputs. For example, we can use an algorithm to find the shortest route between two locations on a map; the same algorithm can be used for any pair of starting and finishing points, so the solution depends on the input to the algorithm. If we know the algorithm for solving a problem then we can solve that problem easily, whenever we want, without having to think! We can just follow the steps. Computers can't think for themselves, so they need to be given algorithms to do things.
Ko te whakaaro hātepe, te tukanga mō te waihanga i ngā hātepe. Ina waihanga te tangata i te hātepe, ki te whakaoti i tētahi rapanga, ka kīia tērā te otinga hātepe.
He torutoru noa iho ngā wāhanga o ngā hātepe tātai (arā, ko ngā momo ka taea te whakahaere ki ngā pūrere matihiko), nā te mea he torutoru noa iho ngā momo tohutohu ka taea e ērā pūrere matihiko te whai; ko ngā mahi matua a aua pūrere matihiko ko te tiki tāuru, te tuku tāputa, te rokiroki i ngā uara, te whai i ngā tohutohu kua raupapangia, te whiriwhiri i ngā kōwhiringa, me te tāruarua i ngā tohutohu kei roto i tētahi koromeke. Ahakoa he ruarua noa iho ngā tohutohu, ko ērā te katoa o ngā āhuatanga ka taea e te pūrere matihiko te tātai, ā, nā tēnei ka kīia ai he whāititanga ō te hātepe i ēnei huānga.
Waitaratanga
Abstraction is all about simplifying things to help us manage complexity. It requires identifying what the most important aspects of a problem are and hiding the other specific details that we don't need to focus on. The important aspects can be used to create a model, or simplified representation, of the original thing we were dealing with. We can then work with this model to solve the problem, rather than having to deal with all the nitty gritty details at once. Computer Scientists often work with multiple levels of abstraction.
Ka whakamahia noatia te waitaratanga e te tangata ia rā, ko tētahi tauira, ko te whakamahi i ngā mahere whenua. Kei te mahere, he whakaaturanga ngāwari o te whenua, me te mahue atu ko ngā mea iti pērā ki ngā rākau maha i te ngahere, ā, ka mau tonu ngā mōhiohiotanga whakahirahira anake e hiahiatia ana e te tangata, pērā ki ngā ingoa o ngā huarahi me ngā rōri.
Ka whakamahi ngā pūrere matihiko i te waitaratanga i ngā wā katoa; ka hunaia ngā mōhiohio take kore e taea ana i te kaiwhakamahi. Hei tauira, ina hiahia koe ki te whakatika i ngā tae o te whakaahua o tō haerenga ki tāwāhi, ka huakina ki te taupānga whakatika pikitia, ka nekehia ngā rēreti tae, ka whakamahia tētahi tātari kano rānei. He maha ngā mahinga whīwhiwhi o te rorohiko, engari ka hunaia te nuinga o ērā.
The picture you took is stored on the computer as a big list of pixels, which are each a different colour, and each colour is represented by a set of numbers, and each of these numbers are stored as binary digits! That's a lot of information. Imagine if when you adjusted the colours you had to go through and look at all the colour values of every pixel and change each and every one of those! That's what the computer is doing for you, but since you don't need to know this to accomplish your goal the computer hides this information away.
Whakamatariki
Ko te whakamatariki te whakawehewehe i te rapanga kia kitea ai ngā wāhanga iti, kia ngāwari ai hoki te whakahaere, kātahi ka taea te whakaoti i ēnei rapanga paku nei. Ka taea te whakawehewehe i ngā rapanga matatini ki ngā wāhanga iti, kia ngāwari ai te whakaoti. Mā te whakakotahi i ēnei otinga e hangaia ai te otinga nui katoa. Mā te whakamatariki e patua ai te taniwha whakamataku o ngā rapanga nui!
Ko te whakamatariki tētahi pūkenga nui hei waihanga hātepe, hei waihanga tukanga hoki e taea ai te whakahaere i ngā pūrere matihiko, nā te mea, me tino whāiti te aronga o ngā tohutohu ki ngā rorohiko. Me āta tohutohu mō ia takahanga paku nei, he whāinga kia tutuki ai ngā mahi.
Hei tauira, ka taea te whakamatariki i te mahi tunu keke, ki ngā mahinga iti iho, kia ngāwari ai te whakaoti i ia wāhanga o te mahi.
Mahi Keke
Tunu Keke
Tukua ngā rawa ki te oko (pata, huka, hēki, puehu paraoa)
Whakaranuhia
Tukua ki te kēne
Whakaurua ki te umu kia 30 miniti te roa
Tangohia i te kēne
Mahia te pani reka
Pania ki runga i te keke
Te whakatau whānui me ngā tauira
Ka kīia hoki te 'whakatau whānui' ko 'te hopu tauira me te whakatau whānui'. Ko te 'whakatau whānui', ko te whakamahinga o tētahi otinga rapanga (he wahanga o te otinga rānei), kātahi ka whakawhānuitia taua otinga kia hāngai ki tētahi atu kaupapa, rapanga rānei, mahi rānei. Nā te mea he hātepe ngā otinga o te pūtaiao rorohiko, ka whakawhānuitia te hātepe kia taea ai te whakamahi i ngā rapanga maha. Ki te whakawhānuitia te hātepe, ka whakamahia te waitaratanga, nā te mea, kia whakawhānuitia tētahi kaupapa, me tango ngā taipitopito e hāngai ana ki ngā horopaki whāiti noa kia waiho ake ai ngā āhuatanga nui o te hātepe. "Ruia taitea, kia tū ko taikaka anake".
Spotting patterns is an important part of this process, when we think about problems we might recognise similarities between them and that they can be solved in similar ways. This is called pattern matching, and it's something we do naturally all the time in our daily life.
Ka taea te hangarua i ngā hātepe whakawhānui mō ngā momo rapanga āhua rite, kia ngāwari ai te waihanga i ngā otinga rapanga hou.
Arotakenga
Mā te arotake, ka rapua ngā otinga e taea ana mō tētahi rapanga, kātahi ka whiriwhiri ko tēhea te otinga pai ake, ko tēhea e hāngai ana ki ētahi horopaki - kaua ki ētahi atu, ā, ka whakaaro hoki me pēhea te whakapai i te otinga kia kaha ake. I a tātou e arotake ana i te otinga, ka whakaaro hoki mō ngā āhuatanga maha. Me whakaaro mō te roa o te wā ka pau kia oti ai te hātepe (tukanga rānei). Ka whakaaro hoki mō te āhei o te hātepe ki te whakaoti i te rapanga, mō te tika, me ngā pānga o te horopaki rerekē. He mahi nui te arotake mā te tangata ia rā ia rā.
There are different ways we can evaluate our algorithmic solutions. We can test their speed by implementing them on a computer; or we can analyse them by counting or calculating how many steps they are likely to take. We can test that our algorithmic solutions work correctly by giving them lots of different inputs, and checking they work as expected. When we do this we need to think about the different inputs we test, because we don't want to check every possible input (often there's an infinite number of possible inputs!), but we still need to know if our algorithmic solutions will work for all inputs. Testing is something Computer Scientists and programmers do all the time. But because we can't usually test every possible input, we also try to evaluate a system using logical reasoning.
Arorau
Ki te whakaoti rapanga, me whakaaro arorau tātou. Ka whakamahia te whakaaro arorau ki te kimi māramatanga, mā te āta titiro, mā te kohikohi raraunga hoki, mā te whakaaro hoki mō ngā mea kei te mōhiotia kētia, kātahi ka whiriwhiri i te otinga i runga i aua mōhiotanga. Mā te whakaaro arorau e pai ake ai te whakamahi mōhiotanga hei waihanga i ngā whakatau, hei arotake hoki i ngā meka.
Hei tauira, mō te waihanga i tētahi papatono e whakatau ana i te ara poto rawa atu i tō whare ki tētahi atu wāhi. Kei te mahere ki raro nei, e 2 ngā miniti ki te whare pukapuka, ina ahu whakateraki atu i tō whare. Ina ahu atu koe ki te tonga, e 3 miniti ki te rīpekatanga o ngā huarahi. Mehemea ka whakaaro koe mō te ara pai e tīmata ai ki te ahu whakatetonga, mā te whakaaro arorau ka mōhio koe, kāore he ara poto ki te tonga nā te mea, ka pau te 3 miniti ki te hīkoi ki te rīpekatanga noa iho.
Mēnā ka hōhonu ake te tirohanga, ka kite tātou ka hangaia tonu ngā rorohiko ki te arorau noa iho. Ka whakamahia ngā uara 'Pono' me te 'Hē', me ngā kīanga 'Boolean' pērā ki te "mēnā pakeke > 5", ki te whakatau i ngā mahi a te papatono rorohiko.
Ki te rapu i te hapa kei roto i tētahi papatono, me whakamahi te whakaaro arorau, kia kimi ai, kei whea, nā te aha hoki i hē ai te mahi a te papatono.
Kāore e taea te tautuhi mō te reo Te Reo Māori, aroha mai!
